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Sensing Matrix optimization for Random Stepped-Frequency Signal Based on Two-Dimensional Ambiguity Function

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Chinese Journal of Electronics 2024年第1期33卷 161-174页

作者： Mingjiu LYU Hao CHEN Jun YANG Xia WU Ming ZHOU Xiaoyan MA Radar NCO School Air Force Early Warning Academy Department of Early Warning Technology Air Force Early Warning Academy

Compressive sensing technique has been widely applied to achieve range-Doppler reconstruction of high frequency radar by utilizing sparse random stepped-frequency(SRSF) signal, which can suppress the complex electromagnetic interference and greatly reduce the coherent processing interval. An important way to improve the performance of sparse signal reconstruction is to optimize the sensing matrix(SM). However, the existing research on the SM optimization needs to design a measurement matrix with superior performance, which needs a large amount of computation and does not consider the influence of the waveform parameters design. In order to improve the superior reconstruction performance, a novel SM optimization approach for SRSF signal is proposed by using two-dimensional ambiguity function(TDAF) in this paper. Firstly, based on the two-dimensional sparse reconstruction model of the SRSFs, the internal relationship between the waveform parameters and the SM was derived. Secondly, the SM optimization problem was directly transformed into the waveform design of SRSFs. Furthermore, on the basis of analyzing the relationship between the mutual coherence matrix of SM and the TDAF matrix of SRSFs, the purpose of optimizing the SM can be achieved by designing the TDAF of the SRSFs. Based on this analysis, a sparse waveform optimization method with joint constraints of maximum and mean sidelobes of the TDAF by using the genetic algorithm was derived. Compared with the traditional SM optimization method, our method not only avoids generating a new measurement matrix, but also further reduces the complexity of the waveform optimization. Simulation experiments verified the effectiveness of the proposed method.

关键词： Correlation Computational modeling Electromagnetic interference optimization methods Signal reconstruction High frequency radar Sensors

Factor graph based navigation and positioning for control system design:A review

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Chinese Journal of Aeronautics 2022年第5期35卷 25-39页

作者： Xiwei WU Bing XIAO Cihang WU Yiming GUO Lingwei LI School of Automation Northwestern Polytechnical UniversityXi’an 710072China

Navigation and positioning is an important and challenging problem in many control engineering *** provides feedback information to design controllers for *** this paper,a bibliographical review on factor graph based navigation and positioning is *** specifically,the sensor modeling,the factor graph optimization methods,and the topology factor based cooperative localization are *** navigation and positioning methods via factor graph are considered and *** in the current research of factor graph based navigation and positioning are also discussed with emphasis on its practical *** limitations of the existing methods,some solutions for future techniques,and recommendations are finally given.

关键词： Factor graph Navigation optimization methods Positioning Sensor modeling

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Open-Source Codes of Topology optimization: A Summary for Beginners to Start Their Research

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Computer Modeling in Engineering & Sciences 2023年第10期137卷 1-34页

作者： Yingjun Wang Xinqing Li Kai Long Peng Wei National Engineering Research Center of Novel Equipment for Polymer Processing The Key Laboratory of Polymer Processing Engineering of the Ministry of EducationGuangdong Provincial Key Laboratory of Technique and Equipment for Macromolecular Advanced ManufacturingSouth China University of TechnologyGuangzhou510641China State Key Laboratory of Alternate Electrical Power Systemwith Renewable Energy Sources North China Electric Power UniversityBeijing102206China State Key Laboratory of Subtropical Building Science School of Civil Engineering and TransportationSouth China University of TechnologyGuangzhou510641China

Topology optimization(TO),a numerical technique to find the optimalmaterial layoutwith a given design domain,has attracted interest from researchers in the field of structural optimization in recent *** beginners,opensource codes are undoubtedly the best alternative to learning TO,which can elaborate the implementation of a method in detail and easily engage more people to employ and extend the *** this paper,we present a summary of various open-source codes and related literature on TO methods,including solid isotropic material with penalization(SIMP),evolutionary method,level set method(LSM),moving morphable components/voids(MMC/MMV)methods,multiscale topology optimization method,***,we classify the codes into five levels,fromeasy to difficult,depending on their difficulty,so that beginners can get started and understand the form of code implementation more quickly.

关键词： Topology optimization open-source code optimization methods code classification beginners

Phishing Websites Detection by Using Optimized Stacking Ensemble Model

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Computer Systems Science & Engineering 2022年第4期41卷 109-125页

作者： Zeyad Ghaleb Al-Mekhlafi Badiea Abdulkarem Mohammed Mohammed Al-Sarem Faisal Saeed Tawfik Al-Hadhrami Mohammad T.Alshammari Abdulrahman Alreshidi Talal Sarheed Alshammari College of Computer Science and Engineering University of Ha'ilHa'il81481KSA College of Computer Sciences and Engineering Hodeidah UniversityHodeidah967Yemen College of Computer Science and Engineering Taibah UniversityAl-Madinah42353KSA Nottingham Trent University MansfieldNG185BHUnited Kingdom

Phishing attacks are security attacks that do not affect only individuals’or organizations’websites but may affect Internet of Things(IoT)devices and *** environment is an exposed environment for such *** may use thingbots software for the dispersal of hidden junk emails that are not noticed by *** and deep learning and other methods were used to design detection methods for these ***,there is still a need to enhance detection *** of an ensemble classiﬁcation method for phishing website(PW)detection is proposed in this study.A Genetic Algo-rithm(GA)was used for the proposed method optimization by tuning several ensemble Machine Learning(ML)methods parameters,including Random Forest(RF),AdaBoost(AB),XGBoost(XGB),Bagging(BA),GradientBoost(GB),and LightGBM(LGBM).These were accomplished by ranking the optimized classi-ﬁers to pick out the best classiﬁers as a base for the proposed method.A PW data-set that is made up of 4898 PWs and 6157 legitimate websites(LWs)was used for this study's *** a result,detection accuracy was enhanced and reached 97.16 percent.

关键词： Phishing websites ensemble classiﬁers optimization methods genetic algorithm

Novel Optimized Feature Selection Using Metaheuristics Applied to Physical Benchmark Datasets

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Computers, Materials & Continua 2023年第2期74卷 4027-4041页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Fadwa Alrowais Sunil Kumar Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt School of Computer Science University of Petroleum and Energy StudiesDehradun248001India Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

In data mining and machine learning,feature selection is a critical part of the process of selecting the optimal subset of features based on the target *** are 2n potential feature subsets for every n features in a dataset,making it difficult to pick the best set of features using standard ***,in this research,a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm(ASSOA)has been *** using metaheuristics to pick features,it is common for the selection of features to vary across runs,which can lead to *** of this,we used the adaptive squirrel search to balance exploration and exploitation duties more evenly in the optimization *** the selection of the best subset of features,we recommend using the binary ASSOA search strategy we developed *** to the suggested approach,the number of features picked is reduced while maximizing classification accuracy.A ten-feature dataset from the University of California,Irvine(UCI)repository was used to test the proposed method’s performance *** other state-of-the-art approaches,including binary grey wolf optimization(bGWO),binary hybrid grey wolf and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hybrid GWO and genetic algorithm 4028 CMC,2023,vol.74,no.2(bGWO-GA),binary firefly algorithm(bFA),and *** results confirm the superiority and effectiveness of the proposed algorithm for solving the problem of feature selection.

关键词： Metaheuristics adaptive squirrel search algorithm optimization methods binary optimizer

Design of a UCA structure with maximum capacity for mm Wave LOS MIMO systems

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Science China(Information Sciences) 2022年第3期65卷 286-287页

作者： Jiancun FAN Hongji LIU Jie LUO Xinmin LUO Jinbo ZHANG The School of Information and Communications Engineering Xi'an Jiaotong University The 54th Research Institute of CETC (CETC-54)

Dear editor,In millimeter wave(mm Wave) systems, traditional multiple input multiple output(MIMO) may become line-of-sight(LOS) MIMO [1], and the rank of the channel matrix using the traditional antenna structure becomes very small [2]. A lower rank implies a low channel capacity [3]. The channel capacity of an LOS MIMO system can be enhanced by adjusting the array diameter of a uniform circular array(UCA), but the channel matrix cannot reach full rank when the UCA contains more than four antennas [4].

关键词： antenna arrays Millimeter wave radio communication optimization methods UCA LOS MIMO

Developer Cooperation Relationship and Attribute Similarity Based Community Detection in Software Ecosystem

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Chinese Journal of Electronics 2023年第1期32卷 39-50页

作者： SHEN Xin DU Junwei GONG Dunwei YAO Xiangjuan School of Information and Control Engineering China University of Mining and Technology School of Information Science and Technology Qingdao University of Science and Technology School of Mathematics China University of Mining and Technology

A software ecosystem(SECO) can be described as a special complex network. Previous complex networks in an SECO have limitations in accurately reflecting the similarity between each pair of nodes. The community structure is critical towards understanding the network topology and function. Many scholars tend to adopt evolutionary optimization methods for community detection. The information adopted in previous optimization models for community detection is incomprehensive and cannot be directly applied to the problem of community detection in an SECO. Based on this, a complex network in SECOs is first built. In the network, the cooperation intensity between developers is accurately calculated, and the attribute contained by each developer is considered. A multi-objective optimization model is formulated. A community detection algorithm based on NSGA-II is employed to solve the above model. Experimental results demonstrate that the proposed method of calculating the developer cooperation intensity and our model are advantageous.

关键词： Biological system modeling Ecosystems optimization methods Complex networks Software Detection algorithms

Mini-batch cutting plane method for regularized risk minimization

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Frontiers of Information Technology & Electronic Engineering 2019年第11期20卷 1551-1563页

作者： Meng-long LU Lin-bo QIAO Da-wei FENG Dong-sheng LI Xi-cheng LU Science and Technology on Parallel and Distributed Laboratory National University of Defense TechnologyChangsha 410073China

Although concern has been recently expressed with regard to the solution to the non-convex problem, convex optimization is still important in machine learning, especially when the situation requires an interpretable model. Solution to the convex problem is a global minimum, and the final model can be explained mathematically. Typically, the convex problem is re-casted as a regularized risk minimization problem to prevent overfitting. The cutting plane method (CPM) is one of the best solvers for the convex problem, irrespective of whether the objective function is differentiable or not. However, CPM and its variants fail to adequately address large-scale data-intensive cases because these algorithms access the entire dataset in each iteration, which substantially increases the computational burden and memory cost. To alleviate this problem, we propose a novel algorithm named the mini-batch cutting plane method (MBCPM), which iterates with estimated cutting planes calculated on a small batch of sampled data and is capable of handling large-scale problems. Furthermore, the proposed MBCPM adopts a "sink" operation that detects and adjusts noisy estimations to guarantee convergence. Numerical experiments on extensive real-world datasets demonstrate the effectiveness of MBCPM, which is superior to the bundle methods for regularized risk minimization as well as popular stochastic gradient descent methods in terms of convergence speed.

关键词： Machine learning optimization methods Gradient methods Cutting plane method

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Modeling and optimization for Scheduling of Chemical Batch Processes

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Chinese Journal of Chemical Engineering 2009年第1期17卷 1-7页

作者：钱宇潘明黄亚才 School of Chemical Engineering SouthChina University of Technology Guangzhou 510640 China

Chemical batch processes have become significant in chemical manufacturing. In these processes, large numbers of chemical products are produced to satisfy human demands in daily life. Recently, economy globalization has resulted, in growing worldwide competitions in *** chemical .process industry. In order to keep competitive in the global marketplace, each company must optimize its production management and set up a reactive system for market fluctuation. Scheduling is the core of production management in chemical processes. The goal of this paper is to review the recent developments in this challenging area. Classifications of batch scheduling problems and optimization methods are introduced. A comparison of six typical models is shown in a general benchmark example from the literature. Finally, challenges and applications in future research are discussed.

关键词： chemical batch processes scheduling optimization methods

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