A Self-Adaptive Particle Swarm Optimization Based Multiple Source Localization Algorithm in Binary Sensor Networks by Long Cheng, Yan Wang, Shuai Li

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A New Hybrid Algorithm for Bankruptcy Prediction Using Switching Particle Swarm Optimization and Support Vector Machines by Yang Lu, Nianyin Zeng, Xiaohui Liu, Shujuan Yi

“…In this paper, a new hybrid algorithm combining switching particle swarm optimization (SPSO) and support vector machine (SVM) is proposed to solve the bankruptcy prediction problem. …”
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Joint Optimization of Multi-Period Empty Container Repositioning and Inventory Control Based on Adaptive Particle Swarm Algorithm by Jiaxin Cai, Ying Huang, Cuijie Diao, Zhihong Jin

“…Secondly, we design an adaptive particle swarm optimization algorithm, introduce dynamic inertia weight and acceleration coefficient adjustment mechanisms, and design heuristic rules for empty container repositioning. …”
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Presenting a Prediction Model for CEO Compensation Sensitivity using Meta-heuristic Algorithms (Genetics and Particle Swarm) by Saeed Khaljastani, Habib Piri, Reza Sotoudeh

“…Given these points, the aim of this research is to provide a model for predicting the sensitivity of CEO compensation using meta-heuristic algorithms, specifically genetic algorithms and particle swarm optimization. …”
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Hybridization of deep learning models with crested porcupine optimizer algorithm-based cybersecurity detection on industrial IoT for smart city environments by Sarah A. Alzakari, Mohammed Aljebreen, Mashael M. Asiri, Wahida MANSOURI, Sultan Alahmari, Mohammed Alqahtani, Shaymaa Sorour, Wafi Bedewi

“…To accomplish that, the CCPOA-HDLM method comprises distinct processes such as min-max normalization, improved Salp swarm algorithm (ISSA)-based feature selection, Multi-Channel Convolutional Neural Network - Recurrent Neural Network (MCNN-RNN)-based cybersecurity detection, and crested porcupine optimizer (CPO)-based parameter selection process. …”
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Fault Diagnosis of High-Power Tractor Engine Based on Competitive Multiswarm Cooperative Particle Swarm Optimizer Algorithm by Maohua Xiao, Weichen Wang, Kaixin Wang, Wei Zhang, Hengtong Zhang

“…First, the USB-CAN device was used to collect data of 8 items of the diesel engine under five different working conditions, and the data was parsed through the SAE J1939 protocol; then, the BP neural network was reconstructed, and a competitive multiswarm cooperative particle swarm optimizer algorithm (COM-MCPSO) was used to optimize its structure and weights. …”
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S-EPSO: A Socio-Emotional Particle Swarm Optimization Algorithm for Multimodal Search in Low-Dimensional Engineering Applications by Raynald Guilbault

“…The first proposed strategy assigns socio-emotional personalities to the particles forming the swarm. The analysis also introduces a technique to help them visit secluded zones. …”
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An Efficient Multisensor Hybrid Data Fusion Approach Based on Artificial Neural Networks and Particle Swarm Optimization Algorithms by Luc Eyembe Ihonock, Jean-François Dikoundou Essiben, Benjamin Salomon Diboma, Joe Suk Yong

“…The preprocessing stage of data is also included in the suggested technique, which starts with the design of the data-collecting device and ends with a hybrid model algorithm. Particle swarm optimization and artificial neural network methods are combined in the hybrid algorithm. …”
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Reliability Analysis of Three-Dimensional Slopes Considering the Soil Spatial Variability Based on Particle Swarm Optimization Algorithm by Xin Chen, Jiale Xu, Yukuai Wan, Rong Yang, Jiewen Sun, Di Wu

“…This paper presents a new algorithm for assessing the reliability of three-dimensional (3D) slope stability considering the spatial variability of soil based on the Particle Swarm Optimization (PSO) algorithm. …”
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Optimization method improvement for nonlinear constrained single objective system without mathematical models by HOU Gong-yu, XU Zhe-dong, LIU Xin, NIU Xiao-tong, WANG Qing-le

“…Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. …”
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A memetic algorithm for high‐strength covering array generation by Xu Guo, Xiaoyu Song, Jian‐tao Zhou, Feiyu Wang, Kecheng Tang, Zhuowei Wang

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Coverage path planning for multi-AUV considering ocean currents and sonar performance by Xukai Mu, Wei Gao

“…To address the CPP of multiple AUVs (multi-AUV) considering both sonar performance and ocean currents, we propose a new integrated algorithm based on the improved Dijkstra algorithm, Particle Swarm Optimization (PSO), and the ELKAI Solve. …”
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A Hybrid Optimization Algorithm for the Synthesis of Sparse Array Pattern Diagrams by Youzhi Liu, Linshu Huang, Xu Xie, Huijuan Ye

“…To comprehensively address the challenges of aperture design, element spacing optimization, and sidelobe suppression in sparse radar array antennas, this paper proposes a hybrid particle swarm optimization (PSO) algorithm that integrates quantum-behavior mechanisms with genetic mutation. …”
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An efficient hybrid algorithm based on particle swarm optimisation and teaching‐learning‐based optimisation for parameter estimation of photovoltaic models by Dianlang Wang, Zhongrui Qiu, Qi Yin, Haifeng Wang, Jing Chen, Chengbi Zeng

“…In order to estimate the unknown parameters of the PV models more precisely and reliably, an efficient hybrid algorithm based on particle swarm optimisation and teaching‐learning‐based optimisation (PSOTLBO) is proposed in this paper. …”
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Optimization of Ship Permanent Magnet Synchronous Motor ADRC Based on Improved QPSO by Hongbo Xu, Jundong Zhang, Jiale Liu, Yang Cao, Ao Ma

“…To address the impact of load variations, external environmental changes, and the tuning of the parameters on Permanent Magnet Synchronous Motors (PMSMs) used in ships, this study proposes an Active Disturbance Rejection Control (ADRC) strategy for PMSMs, optimized by the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm. First, based on the PMSM model, the study addresses the limited disturbance rejection capability of the traditional fal function in the Extended State Observer (ESO) of conventional ADRC. …”
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A Novel Multi-Objective Trajectory Planning Method for Robots Based on the Multi-Objective Particle Swarm Optimization Algorithm by Jiahui Wang, Yongbo Zhang, Shihao Zhu, Junling Wang

“…Secondly, the joint space trajectory of the robot is constructed with fifth-order B-spline functions, realizing the continuous position, velocity, acceleration, and jerk of each joint. Then, the improved multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the trajectory, and the distribution uniformity, convergence, and diversity of the obtained Pareto front are good. …”
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Intrusion Detection-Data Security Protection Scheme Based on Particle Swarm-BP Network Algorithm in Cloud Computing Environment by Zhun Wang, Xue Chen

“…Finally, by introducing the Particle Swarm Optimization (PSO) algorithm into the optimization of the initial weights and thresholds of the BP neural network, the BP neural network is improved based on the momentum factor and adaptive learning rate, and the high detection rate and low false detection rate are realized. …”
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The Optimal Location of Interline Power Flow Controller in the Transmission Lines for Reduction Losses using the Particle Swarm Optimization Algorithm by Mehrdad Ahmadi Kamarposhti

“…This paper proposed, the optimal location of the IPFC in electrical power systems, using the particle swarm optimization algorithm. Expression of sample figure and analysis of the sample system shows that IPFC is effective to minimize the power losses in the power system.…”
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Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

“…This research presents a Particle Swarm Optimization (PSO) algorithm to optimize the deployment of electronic information sensing nodes. …”
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On the optimal control of single-stage hybrid manufacturing systems via novel and different variants of particle swarm optimization algorithm by M. Senthil Arumugam, M. V. C. Rao

“…This paper presents several novel approaches of particle swarm optimization (PSO) algorithm with new particle velocity equations and three variants of inertia weight to solve the optimal control problem of a class of hybrid systems, which are motivated by the structure of manufacturing environments that integrate process and optimal control. …”
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