Evolutionary Computation and Its Applications in Neural and Fuzzy Systems by Biaobiao Zhang, Yue Wu, Jiabin Lu, K.-L. Du

“…Other evolutionary algorithms such as genetic programming, evolutionary programming, particle swarm optimization, immune algorithm, and ant colony optimization are also described. …”
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Research on Mechanical Properties and Parameter Identification of Beam-Column Joint with Gusset Plate Angle Using Experiment and Stochastic Sensitivity Analysis by Xian Dong, Yadi Wang

“…An improved chaotic particle swarm optimization (ICPSO) neural network algorithm was used to study the stochastic sensitivity. …”
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Gauge Deterioration Prediction of Urban Rail Transit Lines Based on CEEMD and SVR by JIA Qingtian, LIN Haijian, JIN Zhong

“…［Method］ CEEMD (complementary ensemble empirical mode decomposition) theory is introduced to extract the IMF (intrinsic mode function) of the geometric alignment of the track section. The PSO (particle swarm optimization) algorithm is utilized to optimize the SVR (support vector regression machine) to train and test the extracted data after calibrating the optimal parameters of the prediction model. …”
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Dynamic Optimization Design of Cranes Based on Human–Crane–Rail System Dynamics and Annoyance Rate by Yunsheng Xin, Gening Xu, Nina Su

“…A dynamic optimization design method for overhead traveling cranes is proposed. A particle swarm optimization (PSO) algorithm was used to optimize the crane structural design, with the structure parameters as the basic variables, the annoyance rate model as the objective function, and the acceleration amplitude and displacement amplitude of the crane as the constraint conditions. …”
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Cost-benefit analysis in demand response with penalty and grid management using blockchain by Manikandan Ramasamy, Thenmalar Kaliannan, Saravanakumar Ramasamy

“…Two distinct optimization methods such as the gray wolf optimization algorithm and particle swarm optimization are employed to solve the optimization model. …”
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Bearing fault diagnosis method based on improved compressed sensing and deep multi-kernel extreme learning machine by FU Qiang, HU Dong, YANG Tongliang, LUO Guoqing, TAN Weimin

“…Subsequently, the compressed data was used as the input signal for the D-MKELM. Particle swarm optimization(PSO) algorithm was applied to optimize critical parameters, enabling intelligent fault diagnosis.ResultsResults demonstrate that the proposed method, using only a small amount of bearing diagnostic data, automatically extracts feature information of bearings from a limited number of measurement signals through the D-MKELM. …”
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Parameter Selection for PSO-Based Hybrid Algorithms and Its Effect on Crack Detection in Cantilever Beams by Amin Ghannadiasl, Saeedeh Ghaemifard

“…The performance of Particle swarm optimization (PSO), Genetic algorithm (GA), Grey wolf optimization (GWO), Firefly algorithm (FA), and hybrid of them base on PSO optimizer to determine the location and depth of crack for cantilever beam are proposed. …”
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A Data-Driven Approach for Reactive Power Optimization Incorporating Interval Values for Renewable Power Generation by Honglei Jia, Cong Zhang, Jieming Du, Na Kuang

“…The proposed method uses an improved particle swarm optimization algorithm to solve the RPO problem. …”
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An Optimization Method of Active Distribution Network Considering Time Variations in Load and Renewable Distributed Generation by Juan Wen, Xing Qu, Siyu Lin, Lin Ding, Lin Jiang

“…The minimum power loss and maximum absorption of RDG power are served as the optimization indexes to construct the dynamic muti-time period optimization model. A hybrid particle swarm optimization (HPSO) algorithm is presented based on integer coding and random coding technique, which can find the most satisfactory solutions for the proposed dynamic model. …”
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Study on the Home Health Caregiver Scheduling Problem under a Resource Sharing Mode considering Differences in Working Time and Customer Satisfaction by Heping Wang, Yuke He, Yan Li, Fuyu Wang

“…Consequently, in this paper, a corresponding mathematical model is established and a hybrid algorithm that combines the whale optimization algorithm (WOA) with the particle swarm optimization (PSO) algorithm is proposed to solve the model. …”
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An Optimization Method of Multiclass Price Railway Passenger Transport Ticket Allocation under High Passenger Demand by Bin Wang, Shaoquan Ni, Fucai Jin, Zixu Huang

“…And we solve this problem by constructing a particle swarm optimization algorithm. Lastly, we use examples to prove that the proposed ticket allocation method can meet the passengers’ needs and have good economic benefits.…”
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Magnetorheological Elastomer Precision Platform Control Using OFFO-PID Algorithm by Ying-Qing Guo, Jie Zhang, Dong-Qing He, Jin-Bao Li

“…In the algorithm, the particle swarm optimization algorithm is used to optimize initial values of the fractional-order PID controller, and the fuzzy algorithm is used to update parameters of the fractional-order PID controller in real time, and the fractional-order PID controller is used to produce the control currents of the MRE devices. …”
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Hardware in the Loop Testing of Adaptive Inertia Weight PSO-Tuned LQR Applied to Vehicle Suspension Control by Joshua Sunder David Reddipogu, Vinodh Kumar Elumalai

“…This paper presents an adaptive inertia weight particle swarm optimization (AIWPSO) employed for solving the multiobjective weight optimization problem of LQR applied for the vehicle active suspension system (ASS). …”
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Optimization of Teaching Evaluation System for Football Professional Teachers Based on Multievaluation Model by Zhiqiang Chen, Qingguo Chen

“…This article explains the origin and characteristics of the particle swarm optimization algorithm and discusses the application status of the PSO algorithm in detail. …”
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Dynamic Prediction of Landslide Displacement Based on Multi-source Time Series by NAN Xiaocong, LIU Junfeng, ZHANG Yongxuan, WANG Yukui

“…Displacement prediction plays an important role in the landslide early warning and forecasting system.In order to improve the accuracy of displacement prediction,a method for dynamic prediction of landslide displacement combining variational modal decomposition (VMD) and double exponential smoothing method (DES) and neural network was proposed.Firstly,the variational modal decomposition was performed on the historical monitoring displacement data to generate multiple modal components,and then the prediction was carried out using the double exponential smoothing method and the extreme learning machine (ELM) model.And the particle swarm optimization algorithm was used to optimize the ELM model to finally accumulate the predicted values of each modal to complete the prediction.Taking the Baijiabao landslide in the Three Gorges reservoir area as an example,the established model was compared with the period terms predicted by least squares support vector machine (LSSVM) and convolutional neural network-gated recurrent unit (CNN-GRU).The results show that the DES-PSO-ELM used can effectively predict the changes of landslide displacement with the of RMSE,root mean square error (RMSE),mean absolute error (MAE),MAPE (mean absolute percentage error) and Pearson correlations of 1.293 mm,0.993 mm,0.008 0 and 0.999 8,respectively,showing minimum prediction errors.The research results can provide a technical basis for the landslide early warning monitoring system.…”
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Simulation Study of Swarm Intelligence Based on Life Evolution Behavior by Yanmin Liu, Ying Bi, Changling Sui, Yuanfeng Luo, Zhuanzhou Zhang, Rui Liu

“…Additionally, PSO is a random swarm intelligence algorithm with the genetic and sociological property, so we embed the improved mutation and crossover operation to particle swarm optimization (PSO) and designed DNA-PSO algorithm to optimize single and multiobjective optimization problems. …”
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Forecasting Renewable energy and electricity consumption using evolutionary hyperheuristic algorithm by Yang Cao, Jun Yu, Rui Zhong, Masaharu Munetomo

“…AE-GAPB integrates a genetic algorithm (GA) at the high-level component and employs particle swarm optimization (PSO) and the bat algorithm (BA) at the low-level component. …”
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Model-free current control solution employing intelligent control for enhanced motor drive performance by Muhammad Usama, Jaehong Kim

“…Additionally, adaptive particle swarm optimization (APSO) is used to optimize the gain parameters of the outer speed control loop for improved dynamic performance. …”
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Optimization of shotcrete manipulator motion trajectory based on AIWCPSO algorithm by SHI Can, TAN Ziliang, LEI Chao, LI Yunwang, XU Hanfei, HU Qiaowei, JI Zhendong

“…To address issues in traditional shotcrete manipulator trajectory planning algorithms, such as abrupt transitions between multiple path segments and low shotcrete efficiency and uniformity caused by frequent starts and stops, an optimized motion trajectory method based on the adaptive inertia weight and acceleration coefficient particle swarm optimization (AIWCPSO) algorithm was proposed. …”
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Verification of Classification Model and Dendritic Neuron Model Based on Machine Learning by Dongbao Jia, Weixiang Xu, Dengzhi Liu, Zhongxun Xu, Zhaoman Zhong, Xinxin Ban

“…Eight learning algorithms including traditional backpropagation, classic evolutionary algorithms such as biogeography-based optimization, particle swarm optimization, genetic algorithm, population-based incremental learning, competitive swarm optimization, differential evolution, and state-of-the-art jSO algorithm are used for training of dendritic neuron model. …”
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