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Optimization of buckling load for laminated composite plates using adaptive Kriging-improved pso:A novel hybrid intelligent method

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Defence Technology（防务技术） 2021年第1期17卷 85-99页

作者： Behrooz Keshtegar Trung Nguyen-Thoi Tam T.Truong Shun-Peng Zhu School of Mechanical and Electrical Engineering University of Electronic Science and Technology of ChinaChengdu611731China Department of Civil Engineering Faculty of EngineeringUniversity of ZabolP.B.***ZabolIran Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityViet Nam

An effective hybrid optimization method is proposed by integrating an adaptive Kriging(A-Kriging)into an improved partial swarm optimization algorithm(Ipso)to give a so-called A-Kriging-Ipso for maximizing the buckling load of laminated composite plates(LCPs)under uniaxial and biaxial *** this method,a novel iterative adaptive Kriging model,which is structured using two training sample sets as active and adaptive points,is utilized to directly predict the buckling load of the LCPs and to improve the efficiency of the optimization *** active points are selected from the initial data set while the adaptive points are generated using the radial random-based convex *** cell-based smoothed discrete shear gap method(CS-DSG3)is employed to analyze the buckling behavior of the LCPs to provide the response of adaptive and input data *** buckling load of the LCPs is maximized by utilizing the Ipso *** demonstrate the efficiency and accuracy of the proposed methodology,the LCPs with different layers(2,3,4,and 10 layers),boundary conditions,aspect ratios and load patterns(biaxial and uniaxial loads)are *** results obtained by proposed method are in good agreement with the literature results,but with less computational *** applying adaptive radial Kriging model,the accurate optimal resultsebased predictions of the buckling load are obtained for the studied LCPs.

关键词： Adaptive kriging Laminated composite plates Buckling optimization Smooth finite element methods Cell-based smoothed discrete shear gap method(CS-DSG3) improved pso

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Application of improved pso-LSSVM on Network Threat Detection

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Wuhan University Journal of Natural Sciences 2013年第5期18卷 418-426页

作者： QI Fumin XIE Xiaoyao JING Fengxuan Key Laboratory of Information and Computing Science Guizhou Province Guizhou Normal University

To solve the problem of the design of classifier in network threat detection, we conduct a simulation experiment for the parameters’ optimal on least squares support vector machine （LSSVM） using the classic pso algorithm, and the experiment shows that uneven distribution of the initial particle swarm exerts a great impact on the results of LSSVM algorithm’s classification. This article proposes an improved pso-LSSVM algorithm based on Divide-and-Conquer （DCpso- LSSVM） to split the optimal domain where the parameters of LSSVM are in. It can achieve the purpose of distributing the initial particles uniformly. And using the idea of Divide-and-Conquer, it can split a big problem into multiple sub-problems, thus, completing problems’ modularization Meanwhile, this paper introduces variation factors to make the particles escape from the local optimum. The results of experiment prove that DCpso-LSSVM has better effect on classification of network threat detection compared with SVM and classic psoLSSVM.

关键词： divide-and-conquer least squares support vector machine (LSSVM) improved pso classification network threat detection

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维普期刊数据库

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Global path planning algorithm based on the Ipso algorithm for USVs

Global path planning algorithm based on the IPSO algorithm f...

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第30届中国控制与决策会议

作者： Jingjing Zhang Xiao Chen Hongning Hu Jianqiang Zhang Lian Wang Naval University of Engineering Unit 91053 of PLA

The global path planning problem of the USV in marine environment has been discussed,a path planning algorithm for USVs based on modeling in polar coordinate system and the improved particle swarm optimization algorithm is ***,considering the global exploration and local development ability of the particle swarm optimization algorithm,the population is initialized by the beta distribution,and the inertia weight is updated by the inverse incomplete function ***,according to the characteristics of particle swarm optimization algorithm,the learning factors of asynchronous changing are designed and the new operator is introduced based on the idea of differential evolution to realize the updating of particle’s velocity and ***,the boundary symmetric mapping strategy is used to deal with the transboundary problem of *** results show that the improved algorithm is superior to the differential evolution algorithm,artificial bee colony optimization algorithm and ordinary particle swarm optimization *** then the Ipso algorithm is introduced into the path planning for the USV,the current position of the USV,the expected position and the distance between the obstacle position are used to determine whether the path planning algorithm should be performed,when the obstacle is encountered,the improved pso algorithm for path planning is resorted to obtain a feasible,shortest and absolutely safe polyline *** results verify the effectiveness of the algorithm.

关键词： improved pso polar coordinate modeling USV path planning

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Formation Tracking and Transformation of AUVs Based on the improved Particle Swarm Optimization Algorithm

Formation Tracking and Transformation of AUVs Based on the I...

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第32届中国控制与决策会议

作者： Yue Li Daqi Zhu Shanghai Engineering Research Center of Intelligent Maritime Search & Rescue and Underwater Vehicles Shanghai Maritime University

A novel algorithm is proposed to solve the problem of formation tracking and formation *** is inspired from the biological principle of particle swarm optimization algorithm(pso).All the AUVs are taken as particles,and key points of virtual formation are taken as one of the navigation targets *** all of the AUVs arrive the desired corresponding key points,the aim of formation tracking is *** the other hand,the formation transformation can be achieved by this algorithm,*** simulations are done to prove the effectiveness of the proposed method.

关键词： improved pso Virtual Formation Formation Tracking and Formation Transformation

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The magnetic levitation ball position control with fuzzy neural network based on particle swarm algorithm

The magnetic levitation ball position control with fuzzy neu...

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第37届中国控制会议

作者： Hao An Jinyu Chen College of Automation Chongqing University

Based on the existing magnetic levitation ball position control algorithm, the fuzzy neural network PID controller using particle swarm optimization is proposed in this paper. The improved particle swarm optimization algorithm is used to optimize the initial parameters of the controller offline, and the gradient descent algorithm is used to train the parameters of network *** simulation shows that the maximum overshot and the adjust time in the proposed controller have a significant improvement,which compared with the traditional PID controller and fuzzy neural network controller, the control precision has been improved,the system has good dynamic performance and steady-state precision.

关键词： improved pso Fuzzy Neural Network Magnetic Levitation Ball Position Control

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