30 Most Down Articles
Published in last 1 year | In last 2 years| In last 3 years| All| Most Downloaded in Recent Month| Most Downloaded in Recent Year|

Most Downloaded in Recent Month
Please wait a minute...
For Selected: Toggle Thumbnails
Optimal production lot size with process deterioration under an extended inspection policy
Hu Fei, Xu Genqi & Ma Lixia
Journal of Systems Engineering and Electronics    2009, 20 (4): 768-776.  
Abstract700)      PDF(pc) (179KB)(10586)       Save

A mathematical model to determine the optimal production lot size for a deteriorating production system under an extended product inspection policy is developed. The last-K product inspection policy is considered so that the nonconforming items can be reduced, under which the last K products in a production lot are inspected and the nonconforming items from those inspected are reworked. Consider that the products produced towards the end of a production lot are more likely to be nonconforming, is proposed an extended product inspection policy for a deteriorating production system. That is, in a production lot, product inspections are performed among the middle K1 items and after inspections, all of the last K2 products are directly reworked without inspections. Our objective here is the joint optimization of the production lot size and the corresponding extended inspection policy such that the expected total cost per unit time is minimized. Since there is no closed form expression for our optimal policy, the existence for the optimal production inspection policy and an upper bound for the optimal lot size are obtained. Furthermore, an efficient solution procedure is provided to search for the optimal policy. Finally, numerical examples are given to illustrate the proposed model and indicate that the expected total cost per unit time of our product inspection model is less than that of the last-K inspection policy.

Related Articles | Metrics
A survey of fine-grained visual categorization based on deep learning
Yuxiang XIE, Quanzhi GONG, Xidao LUAN, Jie YAN, Jiahui ZHANG
Journal of Systems Engineering and Electronics    2024, 35 (6): 1337-1356.   DOI: 10.23919/JSEE.2022.000155
Abstract279)   HTML79)    PDF(pc) (7349KB)(150)       Save

Deep learning has achieved excellent results in various tasks in the field of computer vision, especially in fine-grained visual categorization. It aims to distinguish the subordinate categories of the label-level categories. Due to high intra-class variances and high inter-class similarity, the fine-grained visual categorization is extremely challenging. This paper first briefly introduces and analyzes the related public datasets. After that, some of the latest methods are reviewed. Based on the feature types, the feature processing methods, and the overall structure used in the model, we divide them into three types of methods: methods based on general convolutional neural network (CNN) and strong supervision of parts, methods based on single feature processing, and methods based on multiple feature processing. Most methods of the first type have a relatively simple structure, which is the result of the initial research. The methods of the other two types include models that have special structures and training processes, which are helpful to obtain discriminative features. We conduct a specific analysis on several methods with high accuracy on public datasets. In addition, we support that the focus of the future research is to solve the demand of existing methods for the large amount of the data and the computing power. In terms of technology, the extraction of the subtle feature information with the burgeoning vision transformer (ViT) network is also an important research direction.

Table and Figures | Reference | Related Articles | Metrics
Azimuth-dimensional RCS prediction method based on physical model priors
Jiaqi TAN, Tianpeng LIU, Weidong JIANG, Yongxiang LIU, Yun CHENG
Journal of Systems Engineering and Electronics    2025, 36 (1): 1-14.   DOI: 10.23919/JSEE.2023.000167
Abstract77)   HTML19)    PDF(pc) (4534KB)(38)       Save

The acquisition, analysis, and prediction of the radar cross section (RCS) of a target have extremely important strategic significance in the military. However, the RCS values at all azimuths are hardly accessible for non-cooperative targets, due to the limitations of radar observation azimuth and detection resources. Despite their efforts to predict the azimuth-dimensional RCS value, traditional methods based on statistical theory fails to achieve the desired results because of the azimuth sensitivity of the target RCS. To address this problem, an improved neural basis expansion analysis for interpretable time series forecasting (N-BEATS) network considering the physical model prior is proposed to predict the azimuth-dimensional RCS value accurately. Concretely, physical model-based constraints are imposed on the network by constructing a scattering-center module based on the target scattering-center model. Besides, a superimposed seasonality module is involved to better capture high-frequency information, and augmenting the training set provides complementary information for learning predictions. Extensive simulations and experimental results are provided to validate the effectiveness of the proposed method.

Table and Figures | Reference | Related Articles | Metrics
Rotary unmanned aerial vehicles path planning in rough terrain based on multi-objective particle swarm optimization
Zhen XU, Enze ZHANG, Qingwei CHEN
Journal of Systems Engineering and Electronics    2020, 31 (1): 130-141.   DOI: 10.21629/JSEE.2020.01.14
Abstract621)   HTML15)    PDF(pc) (2868KB)(828)       Save

This paper presents a path planning approach for rotary unmanned aerial vehicles (R-UAVs) in a known static rough terrain environment. This approach aims to find collision-free and feasible paths with minimum altitude, length and angle variable rate. First, a three-dimensional (3D) modeling method is proposed to reduce the computation burden of the dynamic models of R-UAVs. Considering the length, height and tuning angle of a path, the path planning of R-UAVs is described as a tri-objective optimization problem. Then, an improved multi-objective particle swarm optimization algorithm is developed. To render the algorithm more effective in dealing with this problem, a vibration function is introduced into the collided solutions to improve the algorithm efficiency. Meanwhile, the selection of the global best position is taken into account by the reference point method. Finally, the experimental environment is built with the help of the Google map and the 3D terrain generator World Machine. Experimental results under two different rough terrains from Guilin and Lanzhou of China demonstrate the capabilities of the proposed algorithm in finding Pareto optimal paths.

Table and Figures | Reference | Related Articles | Metrics
CONTENTS
Journal of Systems Engineering and Electronics    2025, 36 (1): 0-0.  
Abstract16)      PDF(pc) (127KB)(33)       Save
Related Articles | Metrics
Design of multi-band frequency selective surfaces using multi-periodicity combined elements
Lü Mingyun, Huang Minjie & Wu Zhe
Journal of Systems Engineering and Electronics    2009, 20 (4): 675-680.  
Abstract731)      PDF(pc) (325KB)(1994)       Save

Traditional multi-band frequency selective surface (FSS) approaches are hard to achieve a perfect resonance response in a wide band due to the limit of the onset grating lobe frequency determined by the array. To solve this problem, an approach of combining elements in different period to build a hybrid array is presented. The results of series of numerical simulation show that multi-periodicity combined element FSS, which are designed using this approach, usually have much weaker grating lobes than the traditional FSS. Furthermore, their frequency response can be well predicted through the properties of their member element FSS. A prediction method for estimating the degree of expected grating lobe energy loss in designing multi-band FSS using this approach is provided.

Related Articles | Metrics
Adaptive resource allocation for workflow containerization on Kubernetes
Chenggang SHAN, Chuge WU, Yuanqing XIA, Zehua GUO, Danyang LIU, Jinhui ZHANG
Journal of Systems Engineering and Electronics    2023, 34 (3): 723-743.   DOI: 10.23919/JSEE.2023.000073
Abstract222)   HTML1)    PDF(pc) (7442KB)(459)       Save

In a cloud-native era, the Kubernetes-based workflow engine enables workflow containerized execution through the inherent abilities of Kubernetes. However, when encountering continuous workflow requests and unexpected resource request spikes, the engine is limited to the current workflow load information for resource allocation, which lacks the agility and predictability of resource allocation, resulting in over and under-provisioning resources. This mechanism seriously hinders workflow execution efficiency and leads to high resource waste. To overcome these drawbacks, we propose an adaptive resource allocation scheme named adaptive resource allocation scheme (ARAS) for the Kubernetes-based workflow engines. Considering potential future workflow task requests within the current task pod’s lifecycle, the ARAS uses a resource scaling strategy to allocate resources in response to high-concurrency workflow scenarios. The ARAS offers resource discovery, resource evaluation, and allocation functionalities and serves as a key component for our tailored workflow engine (KubeAdaptor). By integrating the ARAS into KubeAdaptor for workflow containerized execution, we demonstrate the practical abilities of KubeAdaptor and the advantages of our ARAS. Compared with the baseline algorithm, experimental evaluation under three distinct workflow arrival patterns shows that ARAS gains time-saving of 9.8% to 40.92% in the average total duration of all workflows, time-saving of 26.4% to 79.86% in the average duration of individual workflow, and an increase of 1% to 16% in centrol processing unit (CPU) and memory resource usage rate.

Table and Figures | Reference | Related Articles | Metrics
Novel radar dwell scheduling algorithm based on pulse interleaving
Cheng Ting, He Zishu & Tang Ting
Journal of Systems Engineering and Electronics    2009, 20 (2): 247-253.  
Abstract780)      PDF(pc) (1669KB)(1942)       Save

The problem of scheduling radar dwells in multifunction phased array radar systems is addressed. A novel dwell scheduling algorithm is proposed. The whole scheduling process is based on an online pulse interleaving technique. It takes the system timing and energy constraints into account. In order to adapt the dynamic task load, the algorithm considers both the priorities and deadlines of tasks.  The simulation results demonstrate that compared with the conventional adaptive dwell scheduling algorithm, the proposed one can improve the task drop rate and system resource utility effectively.

Related Articles | Metrics
CONTENTS
Journal of Systems Engineering and Electronics    2024, 35 (6): 0-0.  
Abstract33)      PDF(pc) (1747KB)(107)       Save
Related Articles | Metrics
Circular SAR processing using an improved omega-k type algorithm
Leilei Kou, Xiaoqing Wang, Jinsong Chong, Maosheng Xiang, and Minhui Zhu
Journal of Systems Engineering and Electronics    2010, 21 (4): 572-579.   DOI: 10.3969/j.issn.1004-4132.2010.04.008
Abstract1004)      PDF(pc) (1272KB)(2163)       Save
An improved circular synthetic aperture radar (CSAR) imaging algorithm of omega-k (ω-k) type mainly for reconstructing an image on a cylindrical surface is proposed. In the typical CSAR ω-k algorithm, the rage trajectory is approximated by Taylor series expansion to the quadratic terms, which limits the valid synthetic aperture length and the angular reconstruction range severely. Based on the model of the CSAR echo signal, the proposed algorithm directly transforms the signal to the two-dimensional (2D) wavenumber domain, not using approximation processing to the range trajectory. Based on form of the signal spectrum in the wavenumber domain, the formula for the wavenumber domain interpolation of the ω-k algorithm is deduced, and the wavenumber spectrum of the reference point used for bulk compression is obtained from numerical method. The improved CSAR ω-k imaging algorithm increases the valid synthetic aperture length and the angular area greatly and hence improves the angular resolution of the cylindrical imaging. Additionally, the proposed algorithm can be repeated on different cylindrical surfaces to achieve three dimensional (3D) image reconstruction. The 3D spatial resolution of the CSAR system is discussed, and the simulation results validate the correctness of the analysis and the feasibility of the algorithm.

Related Articles | Metrics
Optimal midcourse trajectory cluster generation and trajectory modification for hypersonic interceptions#br#
Humin Lei, Jin Zhou, Dailiang Zhai, Lei Shao, and Dayuan Zhang
Journal of Systems Engineering and Electronics    2017, 28 (6): 1162-1173.   DOI: 10.21629/JSEE.2017.06.14
Abstract446)      PDF(pc) (1478KB)(492)       Save
The hypersonic interception in near space is a great challenge because of the target’s unpredictable trajectory, which demands the interceptors of trajectory cluster coverage of the predicted area and optimal trajectory modification capability aiming at the consistently updating predicted impact point (PIP) in the midcourse phase. A novel midcourse optimal trajectory cluster generation and trajectory modification algorithm is proposed based on the neighboring optimal control theory. Firstly, the midcourse trajectory optimization problem is introduced; the necessary conditions for the optimal control and the transversality constraints are given. Secondly, with the description of the neighboring optimal trajectory existence theory (NOTET), the neighboring optimal control (NOC) algorithm is derived by taking the second order partial derivations with the necessary conditions and transversality conditions. The revised terminal constraints are reversely integrated to the initial time and the perturbations of the co-states are further expressed with the states deviations and terminal constraints modifications. Thirdly, the simulations of two different scenarios are carried out and the results prove the effectiveness and optimality of the proposed method. 
Related Articles | Metrics
Chaos-enhanced moth-flame optimization algorithm for global optimization
Hongwei LI, Jianyong LIU, Liang CHEN, Jingbo BAI, Yangyang SUN, Kai LU
Journal of Systems Engineering and Electronics    2019, 30 (6): 1144-1159.   DOI: 10.21629/JSEE.2019.06.10
Abstract581)   HTML3)    PDF(pc) (563KB)(539)       Save

Moth-flame optimization (MFO) is a novel metaheuristic algorithm inspired by the characteristics of a moth's navigation method in nature called transverse orientation. Like other metaheuristic algorithms, it is easy to fall into local optimum and leads to slow convergence speed. The chaotic map is one of the best methods to improve exploration and exploitation of the metaheuristic algorithms. In the present study, we propose a chaos-enhanced MFO (CMFO) by incorporating chaos maps into the MFO algorithm to enhance its performance. The chaotic map is utilized to initialize the moths' population, handle the boundary overstepping, and tune the distance parameter. The CMFO is benchmarked on three groups of benchmark functions to find out the most efficient one. The performance of the CMFO is also verified by using two real engineering problems. The statistical results clearly demonstrate that the appropriate chaotic map (singer map) embedded in the appropriate component of MFO can significantly improve the performance of MFO.

Table and Figures | Reference | Related Articles | Metrics
Torque estimation for robotic joint with harmonic drive transmission based on system dynamic characteristics
Minghong ZHU, Shu XIAO, Fei YU
Journal of Systems Engineering and Electronics    2022, 33 (6): 1320-1331.   DOI: 10.23919/JSEE.2022.000151
Abstract192)   HTML5)    PDF(pc) (6250KB)(170)       Save

In the applications of joint control and robot movement, the joint torque estimation has been treated as an effective technique and widely used. Researches are made to analyze the kinematic and compliance model of the robot joint with harmonic drive to acquire high precision torque output. Through analyzing the structures of the harmonic drive and experiment apparatus, a scheme of the proposed joint torque estimation method based on both the dynamic characteristics and unscented Kalman filter (UKF) is designed and built. Based on research and scheme, torque estimation methods in view of only harmonic drive compliance model and compliance model with the Kalman filter are simulated as guidance and reference to promote the research on the torque estimation technique. Finally, a promoted torque estimation method depending on both harmonic drive compliance model and UKF is designed, and simulation results compared with the measurements of a commercial torque sensor, have verified the effectiveness of the proposed method.

Table and Figures | Reference | Related Articles | Metrics
Image edge detection based on beamlet transform
Li Jing, Huang Peikang, Wang Xiaohu & Pan Xudong
Journal of Systems Engineering and Electronics    2009, 20 (1): 1-5.  
Abstract954)      PDF(pc) (1461KB)(2153)       Save

Combining beamlet transform with steerable filters, a new edge detection method based on line gradient is proposed. Compared with operators based on point local properties, the edge-detection results with this method achieve higher SNR and position accuracy, and are quite helpful for image registration, object identification, etc. Some edge-detection experiments on optical and SAR images that demonstrate the significant improvement over classical edge operators are also presented. Moreover, the template matching result based on edge information of optical reference image and SAR image also proves the validity of this method.

Related Articles | Metrics
Identity-aware convolutional neural networks for facial expression recognition
Chongsheng Zhang, Pengyou Wang, Ke Chen, and Joni-Kristian K¨am¨ ar¨ainen
Systems Engineering and Electronics    DOI: 10.21629/JSEE.2017.04.18
Doppler estimating and compensating method based on phase
Chen Gang, Zhao Zhengyu, Nie Xuedong, Shi Shuzhu,Yang Guobin & Su Fanfan
Journal of Systems Engineering and Electronics    2009, 20 (4): 681-686.  
Abstract616)      PDF(pc) (195KB)(1918)       Save

According to the Doppler sensitive of the phase coded pulse compression signal, a Doppler estimating and compensating method based on phase is put forward to restrain the Doppler sidelobes, raise the signal-to-noise ratio and improve measuring resolution. The compensation method is used to decompose the echo to amplitude and phase, and then compose the new compensated echo by the amplitude and the nonlinear component of the phase. Furthermore the linear component of the phase can be used to estimate the Doppler frequency shift. The computer simulation and the real data processing show that the method has accurately estimated the Doppler frequency shift, successfully restrained the energy leakage on spectrum, greatly increased the echo signal-to-noise ratio and improved the detection performance of the radio system in both time domain and frequency domain.

Related Articles | Metrics
Detecting JPEG image forgery based on double compression
Wang Junwen, Liu Guangjie, Dai Yuewei & Wang Zhiquan
Journal of Systems Engineering and Electronics    2009, 20 (5): 1096-1103.  
Abstract1017)      PDF(pc) (325KB)(1920)       Save

Detecting the forgery parts from a double compressed image is very important and urgent work for blind authentication. A very simple and efficient method for accomplishing the task is proposed. Firstly, the probabilistic model with periodic effects in double quantization is analyzed, and the probability of quantized DCT coefficients in each block is calculated over the entire image. Secondly, the posteriori probability of each block is computed according to Bayesian theory and the results mentioned in first part. Then the mean and variance of the posteriori probability are to be used for judging whether the target block is tampered. Finally, the mathematical morphology operations are performed to reduce the false alarm probability. Experimental results show that the method can exactly locate the doctored part, and through the experiment it is also found that for detecting the tampered regions, the higher the second compression quality is, the more exact the detection efficiency is.

Related Articles | Metrics
Engineering approach for human error probability quantification
Sun Zhiqiang, Xie Hongwei, Shi Xiujian & Liu Fengqiang
Journal of Systems Engineering and Electronics    2009, 20 (5): 1144-1152.  
Abstract921)      PDF(pc) (325KB)(1932)       Save

A novel approach for engineering application to human error probability quantification is presented based on an overview of the existing human reliability analysis methods. The set of performance shaping factors is classified as two subsets of dominant factors and adjusting factors respectively. Firstly, the dominant factors are used to determine the probabilities of three behavior modes. The basic probability and its interval of human error for each behavior mode are given. Secondly, the basic probability and its interval are modified by the adjusting factors, and the total probability of human error is calculated by a total probability formula. Finally, a simple example is introduced, and the consistency and validity of the presented approach are illustrated.

Related Articles | Metrics
Optimum design of equivalent accelerated life testing plans based on proportional hazards-proportional odds model
Tingting Huang and Tongmin Jiang
Journal of Systems Engineering and Electronics    2011, 22 (5): 871-878.   DOI: 10.3969/j.issn.1004-4132.2011.05.021
Abstract1488)      PDF(pc) (453KB)(1962)       Save
The optimum design of equivalent accelerated life testing plan based on proportional hazards-proportional odds model using D-optimality is presented. The defined equivalent test plan is the test plan that has the same value of the determinant of Fisher information matrix. The equivalent test plan of step stress accelerated life testing (SSALT) to a baseline optimum constant stress accelerated life testing (CSALT) plan is obtained by adjusting the censoring time of SSALT and solving the optimization problem for each case to achieve the same value of the determinant of Fisher information matrix as in the baseline optimum CSALT plan. Numerical examples are given finally which demonstrate the equivalent SSALT plan to the baseline optimum CSALT plan reduces almost half of the test time while achieving approximately the same estimation errors of model parameters.
Related Articles | Metrics
Universal FRFT-based algorithm for parameter estimation of chirp signals
Rong Chen and Yiming Wang
Journal of Systems Engineering and Electronics    2012, 23 (4): 495-501.   DOI: 10.1109/JSEE.2012.00063
Abstract1056)      PDF(pc) (692KB)(2848)       Save

The realization of the parameter estimation of chirp signals using the fractional Fourier transform (FRFT) is based on the assumption that the sampling duration of practical observed signals would be equal to the time duration of chirp signals contained in the former. However, in many actual circumstances, this assumption seems unreasonable. On the basis of analyzing the practical signal form, this paper derives the estimation error of the existing parameter estimation method and then proposes a novel and universal parameter estimation algorithm. Furthermore, the proposed algorithm is developed which allows the estimation of the practical observed Gaussian windowed chirp signal. Simulation results show that the new algorithm works well.

Related Articles | Metrics
Density-based trajectory outlier detection algorithm
Zhipeng Liu, Dechang Pi, and Jinfeng Jiang
Journal of Systems Engineering and Electronics    2013, 24 (2): 335-340.   DOI: 10.1109/JSEE.2013.00042
Abstract667)      PDF(pc) (781KB)(2733)       Save

With the development of global position system (GPS), wireless technology and location aware services, it is possible to collect a large quantity of trajectory data. In the field of data mining for moving objects, the problem of anomaly detection is a hot topic. Based on the development of anomalous trajectory detection of moving objects, this paper introduces the classical trajectory outlier detection (TRAOD) algorithm, and then proposes a density-based trajectory outlier detection (DBTOD) algorithm, which compensates the disadvantages of the TRAOD algorithm that it is unable to detect anomalous defects when the trajectory is local and dense. The results of employing the proposed algorithm to Elk1993 and Deer1995 datasets are also presented, which show the effectiveness of the algorithm.

Related Articles | Metrics
Joint timing synchronization and frequency offset acquisition algorithm for MIMO OFDM systems
Liu Qi & Hu Bo
Journal of Systems Engineering and Electronics    2009, 20 (3): 470-478.  
Abstract773)      PDF(pc) (2313KB)(1111)       Save

For multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, a joint timing synchronization and frequency offset acquisition algorithm based on fractional Fourier transform (FRFT) is proposed. The linear frequency modulation signals superimposed on the data signals are used as the training signals. By performing FRFT on the received signals and searching the peak value of the FRFT results, the receiver can realize timing synchronization and frequency offset acquisition simultaneously. Compared with the existing methods, the proposed algorithm can provide better timing synchronization performance and larger frequency offset acquisition range even under multi-path channels with low signal to noise ratio. Theoretical analysis and simulation results prove this point.

Related Articles | Metrics
Response surface method using grey relational analysis for decision making in weapon system selection
Peng Wang, Peng Meng, and Baowei Song
Journal of Systems Engineering and Electronics    2014, 25 (2): 265-272.   DOI: 10.1109/JSEE.2014.00030
Abstract491)      PDF(pc) (306KB)(4034)       Save

A proper weapon system is very important for a national defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multipleattribute decision making (MADM) problem. This paper proposes a new mathematical model based on the response surface method (RSM) and the grey relational analysis (GRA). RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to analyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.

Related Articles | Metrics
Diffusion mechanism simulation of cloud manufacturing complex network based on cooperative game theory
Chao GENG, Shiyou QU, Yingying XIAO, Mei WANG, Guoqiang SHI, Tingyu LIN, Junjie XUE, Zhengxuan JIA
Journal of Systems Engineering and Electronics    2018, 29 (2): 321-335.   DOI: 10.21629/JSEE.2018.02.13
Abstract385)   HTML1)    PDF(pc) (2605KB)(539)       Save

Cloud manufacturing is a specific implementation form of the "Internet + manufacturing" strategy. Why and how to develop cloud manufacturing platform (CMP), however, remains the key concern of both platform operators and users. A microscopic model is proposed to investigate advantages and diffusion forces of CMP through exploration of its diffusion process and mechanism. Specifically, a three-stage basic evolution process of CMP is innovatively proposed. Then, based on this basic process, a more complex CMP evolution model has been established in virtue of complex network theory, with five diffusion forces identified. Thereafter, simulations on CMP diffusion have been conducted. The results indicate that, CMP possesses better resource utilization, user satisfaction, and enterprise utility. Results of simulation on impacts of different diffusion forces show that both the time required for CMP to reach an equilibrium state and the final network size are affected simultaneously by the five diffusion forces. All these analyses indicate that CMP could create an open online cooperation environment and turns out to be an effective implementation of the "Internet + manufacturing" strategy.

Table and Figures | Reference | Related Articles | Metrics
Resource allocation approach to associate business-IT alignment to enterprise architecture design
Mengmeng ZHANG, Honghui CHEN, Junxian LIU
Journal of Systems Engineering and Electronics    2019, 30 (2): 343-351.   DOI: 10.21629/JSEE.2019.02.13
Abstract364)   HTML1)    PDF(pc) (552KB)(457)       Save

Enterprise architecture (EA) development is always a superior way to address business-IT alignment (BITA) issue. However, most EA design frameworks are inadequate to allocate IT resources, which is an important metric of BITA maturity. Under this situation, the idea of IT resource allocation is combined with the EA design process, in order to extend prior EA research on BITA and to demonstrate EAos capability of implementing IT governance. As an effective resource allocation method, portfolio decision analysis (PDA) is used to align business functions of business architecture and applications of system architecture. Furthermore, this paper exhibits an illustrative case with the proposed framework.

Table and Figures | Reference | Related Articles | Metrics
Multi-QoS routing algorithm based on reinforcement learning for LEO satellite networks
Yifan ZHANG, Tao DONG, Zhihui LIU, Shichao JIN
Journal of Systems Engineering and Electronics    2025, 36 (1): 37-47.   DOI: 10.23919/JSEE.2024.000041
Abstract59)   HTML2)    PDF(pc) (1192KB)(20)       Save

Low Earth orbit (LEO) satellite networks exhibit distinct characteristics, e.g., limited resources of individual satellite nodes and dynamic network topology, which have brought many challenges for routing algorithms. To satisfy quality of service (QoS) requirements of various users, it is critical to research efficient routing strategies to fully utilize satellite resources. This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks, which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources. An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm. Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.

Table and Figures | Reference | Related Articles | Metrics
Membrane-inspired quantum shuffled frog leaping algorithm for spectrum allocation
Hongyuan Gao and Jinlong Cao
Journal of Systems Engineering and Electronics    2012, 23 (5): 679-688.   DOI: 10.1109/JSEE.2012.00084
Abstract783)      PDF(pc) (657KB)(2327)       Save

To solve discrete optimization difficulty of the spectrum allocation problem, a membrane-inspired quantum shuffled frog leaping (MQSFL) algorithm is proposed. The proposed MQSFL algorithm applies the theory of membrane computing and quantum computing to the shuffled frog leaping algorithm, which is an effective discrete optimization algorithm. Then the proposed MQSFL algorithm is used to solve the spectrum allocation problem of cognitive radio systems. By hybridizing the quantum frog colony optimization and membrane computing, the quantum state and observation state of the quantum frogs can be well evolved within the membrane structure. The novel spectrum allocation algorithm can search the global optimal solution within a reasonable computation time. Simulation results for three utility functions of  a cognitive radio system are provided to show that the MQSFL spectrum allocation method is superior to some previous spectrum allocation algorithms based on intelligence computing.

Related Articles | Metrics
Accuracy analysis of a single-fault Markov model for FADEC system
Jing CAI, Wei HU, Kunye CAI
Journal of Systems Engineering and Electronics    2019, 30 (5): 1044-1052.   DOI: 10.21629/JSEE.2019.05.20
Abstract367)   HTML4)    PDF(pc) (1349KB)(318)       Save

Time-limited dispatching (TLD) analysis of the full authority digital engine control (FADEC) systems is an important part of the aircraft system safety analysis and a necessary task for the certification of commercial aircraft and aeroengines. In the time limited dispatch guidance document ARP5107B, a single-fault Markov model (MM) approach is proposed for TLD analysis. However, ARP5107B also requires that the loss of thrust control (LOTC) rate error calculated by applying the single-fault MM must be less than 5% when performing airworthiness certification. Firstly, the sources of accuracy errors in three kinds of MM are analyzed and specified through a case study of the general FADEC system, and secondly a two-fault MM considering maintenance policy is established through analyzing and calculating the expected repair time when two related faults happen. Finally, a specific FADEC system is given to study on the influence factors of accuracy error in the single-fault MM, and the results show that the accuracy error of the single-fault MM decreases with the increase of short or long prescribed dispatch time, and the range values of short time (ST) and long time (LT) are determined to satisfy the requirement of accuracy error within 5%.

Table and Figures | Reference | Related Articles | Metrics
A statistical inference for generalized Rayleigh model under Type-Ⅱ progressive censoring with binomial removals
Junru REN, Wenhao GUI
Journal of Systems Engineering and Electronics    2020, 31 (1): 206-223.   DOI: 10.21629/JSEE.2020.01.20
Abstract503)   HTML2)    PDF(pc) (764KB)(310)       Save

This paper considers the parameters and reliability characteristics estimation problem of the generalized Rayleigh distribution under progressively Type-Ⅱ censoring with random removals, that is, the number of units removed at each failure time follows the binomial distribution. The maximum likelihood estimation and the Bayesian estimation are derived. In the meanwhile, through a great quantity of Monte Carlo simulation experiments we have studied different hyperparameters as well as symmetric and asymmetric loss functions in the Bayesian estimation procedure. A real industrial case is presented to justify and illustrate the proposed methods. We also investigate the expected experimentation time and discuss the influence of the parameters on the termination point to complete the censoring test.

Table and Figures | Reference | Related Articles | Metrics
Sparsity-based efficient simulation of cluster targets electromagnetic scattering
Yuguang TIAN, Yixin LIU, Xuan CHEN, Penghui CHEN, Jun WANG, Junwen CHEN
Journal of Systems Engineering and Electronics    2023, 34 (2): 299-306.   DOI: 10.23919/JSEE.2023.000055
Abstract188)   HTML5)    PDF(pc) (9061KB)(212)       Save

An efficient and real-time simulation method is proposed for the dynamic electromagnetic characteristics of cluster targets to meet the requirements of engineering practical applications. First, the coordinate transformation method is used to establish a geometric model of the observation scene, which is described by the azimuth angles and elevation angles of the radar in the target reference frame and the attitude angles of the target in the radar reference frame. Then, an approach for dynamic electromagnetic scattering simulation is proposed. Finally, a fast-computing method based on sparsity in the time domain, space domain, and frequency domain is proposed. The method analyzes the sparsity-based dynamic scattering characteristic of the typical cluster targets. The error between the sparsity-based method and the benchmark is small, proving the effectiveness of the proposed method.

Table and Figures | Reference | Related Articles | Metrics
UAF-based integration of design and simulation model for system-of-systems
Yimin FENG, Ping GE, Yanli SHAO, Qiang ZOU, Yusheng LIU
Journal of Systems Engineering and Electronics    2025, 36 (1): 108-126.   DOI: 10.23919/JSEE.2025.000022
Abstract49)   HTML1)    PDF(pc) (9662KB)(19)       Save

Model-based system-of-systems (SOS) engineering (MBSoSE) is becoming a promising solution for the design of SoS with increasing complexity. However, bridging the models from the design phase to the simulation phase poses significant challenges and requires an integrated approach. In this study, a unified requirement modeling approach is proposed based on unified architecture framework (UAF). Theoretical models are proposed which compose formalized descriptions from both top-down and bottom-up perspectives. Based on the description, the UAF profile is proposed to represent the SoS mission and constituent systems (CS) goal. Moreover, the agent-based simulation information is also described based on the overview, design concepts, and details (ODD) protocol as the complement part of the SoS profile, which can be transformed into different simulation platforms based on the eXtensible markup language (XML) technology and model-to-text method. In this way, the design of the SoS is simulated automatically in the early design stage. Finally, the method is implemented and an example is given to illustrate the whole process.

Table and Figures | Reference | Related Articles | Metrics
Optimal antenna placement in distributed antenna systems
Zhongzhao Zhang, Zhun Ye, and Weilin Jiang
Journal of Systems Engineering and Electronics    DOI: 10.1109/JSEE.2012.00059
MTSS: multi-path traffic scheduling mechanism based on SDN
Xiaolong XU, Yun CHEN, Liuyun HU, Anup KUMAR
Journal of Systems Engineering and Electronics    2019, 30 (5): 974-984.   DOI: 10.21629/JSEE.2019.05.14
Abstract526)   HTML2)    PDF(pc) (683KB)(544)       Save

Large-scale and diverse businesses based on the cloud computing platform bring the heavy network traffic to cloud data centers. However, the unbalanced workload of cloud data center network easily leads to the network congestion, the low resource utilization rate, the long delay, the low reliability, and the low throughput. In order to improve the utilization efficiency and the quality of services (QoS) of cloud system, especially to solve the problem of network congestion, we propose MTSS, a multi-path traffic scheduling mechanism based on software defined networking (SDN). MTSS utilizes the data flow scheduling flexibility of SDN and the multi-path feature of the fat-tree structure to improve the traffic balance of the cloud data center network. A heuristic traffic balancing algorithm is presented for MTSS, which periodically monitors the network link and dynamically adjusts the traffic on the heavy link to achieve programmable data forwarding and load balancing. The experimental results show that MTSS outperforms equal-cost multi-path protocol (ECMP), by effectively reducing the packet loss rate and delay. In addition, MTSS improves the utilization efficiency, the reliability and the throughput rate of the cloud data center network.

Table and Figures | Reference | Related Articles | Metrics
Using deep learning to detect small targets in infrared oversampling images
Liangkui LIN, Shaoyou WANG, Zhongxing TANG
Journal of Systems Engineering and Electronics    2018, 29 (5): 947-952.   DOI: 10.21629/JSEE.2018.05.07
Abstract593)   HTML8)    PDF(pc) (1235KB)(1007)       Save

According to the oversampling imaging characteristics, an infrared small target detection method based on deep learning is proposed. A 7-layer deep convolutional neural network (CNN) is designed to automatically extract small target features and suppress clutters in an end-to-end manner. The input of CNN is an original oversampling image while the output is a cluttersuppressed feature map. The CNN contains only convolution and non-linear operations, and the resolution of the output feature map is the same as that of the input image. The L1-norm loss function is used, and a mass of training data is generated to train the network effectively. Results show that compared with several baseline methods, the proposed method improves the signal clutter ratio gain and background suppression factor by 3 – 4 orders of magnitude, and has more powerful target detection performance.

Table and Figures | Reference | Related Articles | Metrics
Remaining useful lifetime prediction for equipment based on nonlinear implicit degradation modeling
Zhongyi CAI, Zezhou WANG, Yunxiang CHEN, Jiansheng GUO, Huachun XIANG
Journal of Systems Engineering and Electronics    2020, 31 (1): 194-205.   DOI: 10.21629/JSEE.2020.01.19
Abstract555)   HTML7)    PDF(pc) (597KB)(497)       Save

Nonlinearity and implicitness are common degradation features of the stochastic degradation equipment for prognostics. These features have an uncertain effect on the remaining useful life (RUL) prediction of the equipment. The current data-driven RUL prediction method has not systematically studied the nonlinear hidden degradation modeling and the RUL distribution function. This paper uses the nonlinear Wiener process to build a dual nonlinear implicit degradation model. Based on the historical measured data of similar equipment, the maximum likelihood estimation algorithm is used to estimate the fixed coefficients and the prior distribution of a random coefficient. Using the on-site measured data of the target equipment, the posterior distribution of a random coefficient and actual degradation state are step-by-step updated based on Bayesian inference and the extended Kalman filtering algorithm. The analytical form of the RUL distribution function is derived based on the first hitting time distribution. Combined with the two case studies, the proposed method is verified to have certain advantages over the existing methods in the accuracy of prediction.

Table and Figures | Reference | Related Articles | Metrics
Deep reinforcement learning for UAV swarm rendezvous behavior
Yaozhong ZHANG, Yike LI, Zhuoran WU, Jialin XU
Journal of Systems Engineering and Electronics    2023, 34 (2): 360-373.   DOI: 10.23919/JSEE.2023.000056
Abstract237)   HTML5)    PDF(pc) (6223KB)(317)       Save

The unmanned aerial vehicle (UAV) swarm technology is one of the research hotspots in recent years. With the continuous improvement of autonomous intelligence of UAV, the swarm technology of UAV will become one of the main trends of UAV development in the future. This paper studies the behavior decision-making process of UAV swarm rendezvous task based on the double deep Q network (DDQN) algorithm. We design a guided reward function to effectively solve the problem of algorithm convergence caused by the sparse return problem in deep reinforcement learning (DRL) for the long period task. We also propose the concept of temporary storage area, optimizing the memory playback unit of the traditional DDQN algorithm, improving the convergence speed of the algorithm, and speeding up the training process of the algorithm. Different from traditional task environment, this paper establishes a continuous state-space task environment model to improve the authentication process of UAV task environment. Based on the DDQN algorithm, the collaborative tasks of UAV swarm in different task scenarios are trained. The experimental results validate that the DDQN algorithm is efficient in terms of training UAV swarm to complete the given collaborative tasks while meeting the requirements of UAV swarm for centralization and autonomy, and improving the intelligence of UAV swarm collaborative task execution. The simulation results show that after training, the proposed UAV swarm can carry out the rendezvous task well, and the success rate of the mission reaches 90%.

Table and Figures | Reference | Related Articles | Metrics
Leader trajectory planning method considering constraints of formation controller
Dongdong YAO, Xiaofang WANG, Hai LIN, Zhuping WANG
Journal of Systems Engineering and Electronics    2023, 34 (5): 1294-1308.   DOI: 10.23919/JSEE.2023.000079
Abstract165)   HTML0)    PDF(pc) (8384KB)(127)       Save

To ensure safe flight of multiple fixed-wing unmanned aerial vehicles (UAVs) formation, considering trajectory planning and formation control together, a leader trajectory planning method based on the sparse A* algorithm is introduced. Firstly, a formation controller based on prescribed performance theory is designed to control the transient and steady formation configuration, as well as the formation forming time, which not only can form the designated formation configuration but also can guarantee collision avoidance and terrain avoidance theoretically. Next, considering the constraints caused by formation controller on trajectory planning such as the safe distance, turn angle and step length, as well as the constraint of formation shape, a leader trajectory planning method based on sparse A* algorithm is proposed. Simulation results show that the UAV formation can arrive at the destination safely with a short trajectory no matter keeping the formation or encountering formation transformation.

Table and Figures | Reference | Related Articles | Metrics
Intelligent modeling method for OV models in DoDAF2.0 based on knowledge graph
Yue ZHANG, Jiang JIANG, Kewei YANG, Xingliang WANG, Chi XU, Minghao LI
Journal of Systems Engineering and Electronics    2025, 36 (1): 139-154.   DOI: 10.23919/JSEE.2024.000034
Abstract30)   HTML1)    PDF(pc) (8177KB)(17)       Save

Architecture framework has become an effective method recently to describe the system of systems (SoS) architecture, such as the United States (US) Department of Defense Architecture Framework Version 2.0 (DoDAF2.0). As a viewpoint in DoDAF2.0, the operational viewpoint (OV) describes operational activities, nodes, and resource flows. The OV models are important for SoS architecture development. However, as the SoS complexity increases, constructing OV models with traditional methods exposes shortcomings, such as inefficient data collection and low modeling standards. Therefore, we propose an intelligent modeling method for five OV models, including operational resource flow OV-2, organizational relationships OV-4, operational activity hierarchy OV-5a, operational activities model OV-5b, and operational activity sequences OV-6c. The main idea of the method is to extract OV architecture data from text and generate interoperable OV models. First, we construct the OV meta model based on the DoDAF2.0 meta model (DM2). Second, OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field (BiLSTM-CRF) model. And OV architecture relationships are collected with relationship extraction rules. Finally, we define the generation rules for OV models and develop an OV modeling tool. We use unmanned surface vehicles (USV) swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.

Table and Figures | Reference | Related Articles | Metrics
3D face registration based on principal axis analysis and labeled regions orientation
Guo Zhe, Zhang Yanning, Lin Zenggang & Liu Yantong
Journal of Systems Engineering and Electronics    2009, 20 (6): 1324-1331.  
Abstract786)      PDF(pc) (456KB)(395)       Save

A novel multi-view 3D face registration method based on principal axis analysis and labeled regions orientation called local orientation registration is proposed. The pre-registration is achieved by transforming the multi-pose models to the standard frontal model’s reference frame using the principal axis analysis algorithm. Some significant feature regions, such as inner and outer canthus, nose tip vertices, are then located by using geometrical distribution characteristics. These regions are subsequently employed to compute the conversion parameters using the improved iterative closest point algorithm, and the optimal parameters are applied to complete the final registration. Experimental results implemented on the proper database demonstrate that the proposed method significantly outperforms others by achieving 1.249 and 1.910 mean root-mean-square measure with slight and large view variation models, respectively.

Related Articles | Metrics
PID-type fault-tolerant prescribed performance control of fixed-wing UAV
Ziquan YU, Youmin ZHANG, Bin JIANG
Journal of Systems Engineering and Electronics    2021, 32 (5): 1053-1061.   DOI: 10.23919/JSEE.2021.000090
Abstract373)   HTML2)    PDF(pc) (3842KB)(161)       Save

This paper introduces a fault-tolerant control (FTC) design for a faulty fixed-wing unmanned aerial vehicle (UAV). To constrain tracking errors against actuator faults, error constraint inequalities are first transformed to a new set of variables based on prescribed performance functions. Then, the commonly used and powerful proportional-integral-derivative (PID) control concept is employed to filter the transformed error variables. To handle the fault-induced nonlinear terms, a composite learning algorithm consisting of neural network and disturbance observer is incorporated for increasing flight safety. It is shown by Lyapunov stability analysis that the tracking errors are strictly constrained within the specified error bounds. Experimental results are presented to verify the feasibility of the developed FTC scheme.

Table and Figures | Reference | Related Articles | Metrics