CNN-LSTM-Attention with PSO optimization for temperature and fault prediction in meat grinder motors by Yao Zhang, Pengfei Zhang, Wenchao Zhang, Mingwei Wang

“…In this paper, a deep learning model, CNN-LSTM-AP, is developed, combining convolutional neural network (CNN), long short-term memory network (LSTM), attention mechanism (Attention), and particle swarm optimization (PSO). The Attention mechanism is used to assign weights to input features, enhancing the model focus on important data. …”
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Distribution Network Reconfiguration Using Selective Firefly Algorithm and a Load Flow Analysis Criterion for Reducing the Search Space by Cassio Gerez, Lindenberg I. Silva, Edmarcio A. Belati, Alfeu J. Sguarezi Filho, Eduardo C. M. Costa

“…Results found for simulations with 33, 70, and 84 buses are presented and comparisons with selective particle swarm optimization (SPSO) and selective bat algorithm (SBAT) are made.…”
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Optimizing electric vehicle energy consumption prediction through machine learning and ensemble approaches by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adeeb Noor, Sufyan Ali Memon

“…The K-Nearest Neighbors (KNN) algorithm is employed as the base model, with hyperparameter optimization performed using GridSearchCV, RandomizedSearchCV, Optuna, and Particle Swarm Optimization (PSO). …”
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A multi-strategy improved snake optimizer and its application to SVM parameter selection by Hong Lu, Hongxiang Zhan, Tinghua Wang

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A comprehensive review of AI and machine learning techniques in antenna design optimization and measurement by Pradnya A. Gajbhiye, Satya P. Singh, Madan Kumar Sharma

“…This review examines the latest advancements in applying AI/ML approaches to antenna design optimization. It explores the use of various AI/ML algorithms such as neural networks, decision trees, genetic algorithms, and particle swarm optimization in this context. …”
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Applying an optimized low risk model for fast history matching in giant oil reservoir by Mojtaba karimi, Ali Mortazavi, Mohammad Ahmadi

“…Finally, the process was optimized by two main algorithms for reaching best solutions which are genetic and particle swarm optimization. …”
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Multiobjective Demand Double-Layer Energy Consumption Optimization Strategy for Microgrid Based on Improved HPSOFA by Bin Zhang, Jue Wang, Bo Li

“…In order to optimize the economy and environmental protection of microgrid, this paper establishes a demand response model based on comprehensive satisfaction, combines the advantages of the classical multiobjective particle swarm algorithm and multiobjective firefly algorithm, and proposes a hybrid particle swarm optimization and firefly algorithm (HPSOFA) to solve the joint economic and environmental dispatch problem of microgrid and improve the wind and light consumption capacity. …”
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Reliability evaluation and multi-objective optimization of combustion chamber’s key components of marine engine by Lei Hu, Wentong Wang, Xu Wang, Jianguo Yang, Yonghua Yu, Chunyang Mei

“…The research shows that the multi-objective particle swarm optimization algorithm achieves the best performance, the maximum temperatures of the piston, cylinder head, and liner decrease by 3.90 %, 5.66 %, and 6.52 %, the maximum thermo-mechanical coupling stresses reduced by 9.41 %, 7.83 %, and 4.97 % respectively, and creep-fatigue life enhancements reach 3.84 % and 12.67 % for the piston and cylinder head. …”
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Research on optimization technology of new pipeline design for regional natural gas pipeline network by Jingyi CUI, Kunfeng ZHU, Cuixian GAO, Li GU, Jing REN, Yuxing LI, Wuchang WANG

“…Secondly, a particle swarm optimization algorithm was utilized for model solution optimization. …”
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Adaptive mechanism-based grey wolf optimizer for feature selection in high-dimensional classification. by Genliang Li, Yaxin Cui, Jingyu Su

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Magnetic targets positioning method based on multi-strategy improved Grey Wolf optimizer by Binjie Lu, Zongji Li, Xiaobing Zhang

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An Investigation into the Rescue-Path Planning Algorithm for Multiple Mine Rescue Teams Based on FA-MDPSO and an Improved Force-Directed Layout by Qiangyu Zheng, Peijiang Ding, Zhixin Qin, Zhenguo Yan

“…Subsequently, the hyperparameters of MDPSO (Multiple Constraints Discrete Particle Swarm Optimisation) were optimised by means of four intelligent algorithms—ACO (Ant Colony Optimization), FA (Firefly Algorithm), GWO (Grey Wolf Optimizer) and WOA (Whale Optimization Algorithm). …”
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Maximizing Energy Output of Photovoltaic Systems: Hybrid PSO-GWO-CS Optimization Approach by Hassan S. Ahmed, Ahmed J. Abid, Adel A. Obed, Ameer L. Saleh, Reheel J. Hassoon

“…This study aims to address these challenges by combining cuckoo search (CS), gray wolf optimization (GWO), and particle swarm optimization (PSO) to enhance MPPT performance. …”
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Tooth Profile Modification Method of RV Reducer Cycloid Gear Aiming at Optimizing Carrying Capacity by Zongwen An, Panlong Jia, Qiang Wang, Zhili Li, Mingyuan Lei

“…Cycloid gear tooth profile modification is very important to the performance of RV reducer，in order to select the shape modification method and parameter size reasonably and improve the stress state of the cycloid tooth surface，an equidistant & radical-moving modification method based on particle swarm optimization algorithm to optimize bearing capacity is proposed. …”
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Optimization of high-dimensional expensive multi-objective problems using multi-mode radial basis functions by Jiangtao Shen, Xinjing Wang, Ruixuan He, Ye Tian, Wenxin Wang, Peng Wang, Zhiwen Wen

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Multi-layer Embedded Optimization of Microgrid Capacity Considering Price and Incentive/Compensation Coupling Mechanism by Xianhui ZHU, Xu HU, Nan SHI, Yao ZHANG, Jingwen ZHONG

“…Finally, the optimization models of both the source and load are coupled through the multi-layer embedded mechanism, and a solution model is constructed, which combines the multi-objective particle swarm optimization (MOPSO) algorithm and the particle swarm optimization–imperial competition algorithm (PSO-ICA). …”
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Design and parameter optimization of PBC-NDO composite controller for electric vehicle wireless charging system by YAN Rongge, YAN Chunjiao, YANG Qingxin, ZHANG Xian

“…Aiming at the problems that the charging voltage of the wireless charging system of electric vehicle is unstable due to the offset of the primary and secondary coils and load fluctuation in the process of variable voltage intermittent fast charging, and the controller parameters are mostly selected by empirical value and trial and error method, a composite control strategy combining passivity based controller (PBC) and nonlinear disturbance observer (NDO) based on particle swarm optimization algorithm is proposed. …”
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An integrated optimization model of network behavior victimization identification based on association rule feature extraction by Shengli ZHOU, Linqi RUAN, Rui XU, Xikang ZHANG, Quanzhe ZHAO, Yuanbo LIAN

“…The identification of the risk of network behavior victimization was of great significance for the prevention and warning of telecom network fraud.Insufficient mining of network behavior features and difficulty in determining relationships, an integrated optimization model for network behavior victimization identification based on association rule feature extraction was proposed.The interactive traffic data packets generated when users accessed websites were captured by the model, and the implicit and explicit behavior features in network traffic were extracted.Then, the association rules between features were mined, and the feature sequences were reconstructed using the FP-Growth algorithm.Finally, an analysis model of telecom network fraud victimization based on network traffic analysis was established, combined with the stochastic forest algorithm of particle swarm optimization.The experiments show that compared with general binary classification models, the proposed model has better precision and recall rates and can effectively improve the accuracy of network fraud victimization identification.…”
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FAULT DIAGNOSIS OF RECIPROCATING COMPRESSOR ON THE RESONANCE-BASED SPARSE SIGNAL DECOMPOSITION WITH OPTIMAL Q-FACTOR by WANG JinDong, BU QingChao, ZHAO HaiYang, ZHANG HongBin

“…Reciprocating compressor vibration signal is typical nonlinear and non-stationary,and the vibration information interference coupling, owing to this problem,a fault diagnosis method of reciprocating compressor on the resonance-based sparse signal decomposition with optimal Q-factor was proposed.The method use resonance sparse decomposition to find the low resonance component which its kurtosis is maximum, optimize Q-factor with genetic algorithm and particle swarm optimization to get the optimal Q-factor;then use resonance sparse decomposition to decompose reciprocating compressor vibration signal by the optimal Q-factor;the result shows that this method can diagnose the oversized bearing clearance fault effectively.…”
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Harnessing greylag goose optimization for efficient MPPT and seven-level inverter in renewable energy systems by K. Rajaram, R. Kannan

“…The proposed MPPT-based seven-level invertersystem was simulated using MATLAB. The proposed GGO algorithm achieved a minimal THD of 1.95%, surpassing methods such as salp swarm optimization (6.14%), artificial neural networks with fuzzy logic (5.9%), hybrid global selective algorithm (GSA) selective harmonic elimination (7.7%), and genetic algorithms with particle swarm optimization (10.84%), demonstrating its exceptional efficacy in improving power quality.…”
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