A Mobile Robot Path Planning Method Based on Dynamic Multipopulation Particle Swarm Optimization by Yunjie Zhang, Ning Li, Yadong Chen, Zhenjian Yang, Yue Liu

“…To overcome the limitations of particle swarm optimization (PSO) in mobile robot path planning, including issues such as premature convergence and sensitivity to local optima, this study proposes a novel approach, dynamic multipopulation particle swarm optimization (DMPSO). …”
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Enhancing Speech Recognition Using Improved Particle Swarm Optimization Based Hidden Markov Model by Lokesh Selvaraj, Balakrishnan Ganesan

“…In this paper a novel speech recognition method based on vector quantization and improved particle swarm optimization (IPSO) is suggested. The suggested methodology contains four stages, namely, (i) denoising, (ii) feature mining (iii), vector quantization, and (iv) IPSO based hidden Markov model (HMM) technique (IP-HMM). …”
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Unified Resource Allocation and Mobility Management Technique Using Particle Swarm Optimization for VLC Networks by Muhammet Selim Demir, Sadiq M. Sait, Murat Uysal

“…In this paper, we present a unified resource allocation and mobility management algorithm based on particle swarm optimization (PSO) for indoor visible light communication (VLC) networks. …”
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Facial recognition optimization based on adversarial sample generation in the field of artificial intelligence by Jie Yang

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A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization by Lizhi Cui, Zhihao Ling, Josiah Poon, Simon K. Poon, Junbin Gao, Paul Kwan

“…This paper proposes a separation method, based on the model of Generalized Reference Curve Measurement and the algorithm of Particle Swarm Optimization (GRCM-PSO), for the High Performance Liquid Chromatography with Diode Array Detection (HPLC-DAD) data set. …”
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GMM-based localization algorithm under NLOS conditions by Wei CUI, Cheng-dong WU, Yun-zhou ZHANG, Zi-xi JIA, Long CHENG

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Multi-modal prediction of breast cancer using particle swarm optimization with non-dominating sorting by Vijayalakshmi S, John A, Sunder R, Senthilkumar Mohan, Sweta Bhattacharya, Rajesh Kaluri, Guang Feng, Usman Tariq

“…The experimental results of the study are evaluated against the state-of-the-art algorithms, namely, genetic algorithm kernel density estimation and particle swarm optimization kernel density estimation wherein the results justify the superiority of the proposed model.…”
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Control and Stability Analysis of Double Time-Delay Active Suspension Based on Particle Swarm Optimization by Kaiwei Wu, Chuanbo Ren

“…Aiming at the application of time-delay feedback control in vehicle active suspension systems, this paper has researched the dynamic behavior of semivehicle four-degree-of-freedom structure including an active suspension with double time-delay feedback control, focusing on analyzing the vibration response and stability of the main vibration system of the structure. The optimal objective function is established according to the amplitude-frequency characteristics of the system, and the optimal time-delay control parameters are obtained by using the particle swarm optimization algorithm. …”
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Hydropower Plant Available Energy Forecasting Using Artificial Neural Network and Particle Swarm Optimization by Suriya Kaewarsa, Vanhkham Kongpaseuth

“…Considering the fluctuation and nonlinearity of data which significantly influence the forecasting results, this study develops an effective hybrid model by integrating an Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) called “PSO-ANN” model based on the hydrological and meteorological data pre-processed by cross-correlation function (CCF), autocorrelation function (AFC), and normalization techniques for predicting the available energy portion corresponding to the reservoir inflow mentioned above for a case study hydropower plant in Laos, namely, the Theun-Hinboun hydropower plant (THHP). …”
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Permeability Predictions for Tight Sandstone Reservoir Using Explainable Machine Learning and Particle Swarm Optimization by Jing-Jing Liu, Jian-Chao Liu

“…Based on the data preprocessing, global and local interpretations are performed according to the Shapley additive explanations (SHAP) analysis, and the redundant features in the data set are screened to identify the porosity, AC, CAL, and GR slope as the four most important features. The particle swarm optimization algorithm is then used to optimize the hyperparameters of the XGBoost model. …”
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Hybrid Particle Swarm and Differential Evolution Algorithm for Solving Multimode Resource-Constrained Project Scheduling Problem by Lieping Zhang, Yingxiong Luo, Yu Zhang

“…In order to find a feasible solution for the multimode resource-constrained project scheduling problem (MRCPSP), a hybrid of particle swarm optimization (PSO) and differential evolution (DE) algorithm is proposed in this paper. …”
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Credit card fraud Detection using Feature select method and improved machine learning algorithm by Mohammed AL-Hammadi

“…The SVM classification model then performs the final classification, with its hyperparameters optimized through the particle swarm optimization (PSO) technique. …”
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Silicon Mode (de)Multiplexer Based on Cascaded Particle-Swarm-Optimized Counter-Tapered Couplers by Weiwei Chen, Hongxiang Li, Bohao Zhang, Pengjun Wang, Shixun Dai, Yuxiao Liu, Jun Li, Yan Li, Qiang Fu, Tingge Dai, Hui Yu, Jianyi Yang

“…In this paper, a design of a silicon mode (de)multiplexer based on cascaded counter-tapered couplers is proposed and investigated. By using the particle swarm optimization algorithm and finite difference time domain method, structural parameters of each counter-tapered coupler in our proposed mode (de)multiplexer are optimized so that high conversion efficiencies can be obtained and coupling lengths can be significantly shortened. …”
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Hybrid Swarm Intelligence and Human-Inspired Optimization for Urban Drone Path Planning by Yidao Ji, Qiqi Liu, Cheng Zhou, Zhiji Han, Wei Wu

“…Urban drone applications require efficient path planning to ensure safe and optimal navigation through complex environments. Drawing inspiration from the collective intelligence of animal groups and electoral processes in human societies, this study integrates hierarchical structures and group interaction behaviors into the standard Particle Swarm Optimization algorithm. …”
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Short term traffic flow prediction and timing optimization at signalized intersections based on SG-LSTM and particle swarm optimization by Lei Yang, Ruijun Guo

“…The Pareto compromise programming method is employed to perform dimensionless processing of the three performance indicators, while the fuzzy preference method is utilized to ascertain the weight relationships among the objective functions. The optimized signal timing scheme is derived through the implementation of the particle swarm optimization algorithm in Matlab. …”
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Analysis on Solar Panel Crack Detection Using Optimization Techniques by M.D. Dafny Lydia, K. Sri Sindhu, K. Gugan

“…Crack can be distinguished by utilizing optimization techniques based on segmentation. The optimization techniques are Particle Swarm Optimization (PSO), Differential Particle Swarm Optimization (DPSO) and Fractional Order Differential Particle Swarm Optimization (FODPSO). …”
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Performance Analysis of a Semiactive Suspension System with Particle Swarm Optimization and Fuzzy Logic Control by Abroon Jamal Qazi, Clarence W. de Silva, Afzal Khan, Muhammad Tahir Khan

“…It is able to handle nonlinearities through the use of heuristic rules. Particle swarm optimization (PSO) is applied to determine the optimal gain parameters for the fuzzy logic controller, while maintaining within the normalized ranges of the controller inputs and output. …”
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Interpretability-Oriented Adjustment of K-Means: A Multiple-Objective Particle Swarm Optimization Framework by Liang Chen, Leming Sun, Caiming Zhong

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Optimal power allocation in spatial MIMO channel using heuristic algorithms by Javad Zeraatkar Moghaddam, Hamid Farrokhi

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Comparative Study of Swarm-Based Algorithms for Location-Allocation Optimization of Express Depots by Yong-Wei Zhang, Qin Xiao, Xue-Ying Sun, Liang Qi

“…The proposed encoding scheme is verified on particle swarm optimization, differential evolution, artificial bee colony, and powerful differential evolution variant, and the performances are compared to those of the traditional encoding scheme. …”
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