The authentication of Yanchi tan lamb based on lipidomic combined with particle swarm optimization-back propagation neural network by Qi Yang, Dequan Zhang, Chongxin Liu, Le Xu, Shaobo Li, Xiaochun Zheng, Li Chen

“…This study successfully combined widely targeted lipidomic with a back propagation (BP) neural network optimized based on a particle swarm algorithm to identify the authenticity of Yanchi Tan lamb. …”
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A Wi-Fi Indoor Localization Strategy Using Particle Swarm Optimization Based Artificial Neural Networks by Nan Li, Jiabin Chen, Yan Yuan, Xiaochun Tian, Yongqiang Han, Mingzhe Xia

“…In this paper, we propose an indoor localization system using the affinity propagation (AP) clustering algorithm and the particle swarm optimization based artificial neural network (PSO-ANN). …”
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Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

“…Circulating current arises from the mismatch between submodule capacitor voltages and the DC terminals. This paper uses a particle swarm optimisation (PSO) algorithm to determine the optimal values for the injected components. …”
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Risk prediction of hyperuricemia based on particle swarm fusion machine learning solely dependent on routine blood tests by Min Fang, Chengjie Pan, Xiaoyi Yu, Wenjuan Li, Ben Wang, Huajian Zhou, Zhenying Xu, Genyuan Yang

“…Subsequently, a risk prediction model is constructed based on the parameter optimization of five machine learning models using the PSO algorithm. The accuracy and sensitivity of the proposed particle swarm fusion Stacking model reach 97.8% and 97.6%, marking an improvement in accuracy of over 11% compared to the state-of-the-art models. …”
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Load optimization of cogeneration units based on intuitive multi-objective fish swarm algorithm by Xueqiang Shen, Jiaxin Wang

“…It dynamically categorizes swarm particles into three states, improving solution space coverage and priority-based solution identification. …”
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FAULT DIAGNOSIS METHOD OF SUBMERSIBLE SEWAGE PUMP BASED ON IMPROVED HOPFIELD NEURAL NETWORK by WANG Hui, LI NanQi, YANG ZhiPeng, ZHAO GuoChao, TIAN LiYong

“…The connection weights of HNN neural network were optimized by particle swarm optimization（PSO） algorithm to improve the global convergence ability of the improved neural network, and the improved HNN neural network model was obtained. …”
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A Novel Algorithm for Enhancing Terrain-Aided Navigation in Autonomous Underwater Vehicles by Dan Wang, Liqiang Liu, Yueyang Ben, Liang Cao, Zhongge Dong

“…To enhance the matching accuracy under large initial position errors, an improved terrain matching algorithm comprising terrain contour matching (TERCOM), particle swarm optimization (PSO), and iterative closest contour point (ICCP), named TERCOM-PSO-ICCP, is proposed. …”
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Improvement of the Voltage Profile and Loss Reduction in Distribution Network Using Moth Flame Algorithm: Wolaita Sodo, Ethiopia by S. Balakumar, Akililu Getahun, Samuel Kefale, K. Ramash Kumar

“…There are several techniques that emerged to solve problems in the power system to provide quality and uninterrupted supply to customers. The algorithms used in this paper to determine the appropriate location and size of the Static Var Compensator (SVC) in the Distribution Network (DN) are Moth Flame Optimization (MFO) and Particle Swarm Optimization (PSO). …”
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Fog node intrusion detection and response based on SVMIF and INSGA-II algorithm by Zhuojun Luo

“…Additionally, modified particle swarm optimization was employed to optimize the model's parameters. …”
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A Meta-Heuristic Algorithm-Based Feature Selection Approach to Improve Prediction Success for Salmonella Occurrence in Agricultural Waters by Murat Canayaz, Murat Demir, Zeynal Topalcengiz

“…Meta-heuristic optimization algorithms had a positive effect on improving Salmonella prediction success in agricultural waters despite spatio-temporal variations. …”
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Dynamic arithmetic optimization algorithm control of distributed generations for demand balancing and enhancing power quality of unbalanced distribution systems by Ahmad Eid, Abdulrahman Alsafrani

“…Each system phase has its own DG. Particle Swarm Optimization (PSO) and Dynamic Arithmetic Optimization Algorithm (DAOA) determine each phase’s best locations, sizes, and power factors. …”
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System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario by Wenhao Luo, Yuan Zeng, Ximeng Zheng, Lingyan Zha, Weicheng Cai, Qing Wang, Jingjin Zhang

“…Finally, a network coverage optimization scheme was designed by combining a particle swarm optimization (PSO) algorithm and link quality prediction model, and a reliable cluster routing protocol was designed by combining K-means algorithm. …”
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Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems by Thang Trung Nguyen, Thai Dinh Pham, Le Chi Kien, Le Van Dai

“…Furthermore, we have also applied five other metaheuristic algorithms consisting of biogeography-based optimization (BBO), genetic algorithm (GA), particle swarm optimization algorithm (PSO), sunflower optimization (SFO), and salp swarm algorithm (SSA) for dealing with the same problem and evaluating further performance of ICOA. …”
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Large Data Oriented to Image Information Fusion Spark and Improved Fruit Fly Optimization Based on the Density Clustering Algorithm by Yanfang Zhang

“…Then, a hybrid fruit fly particle swarm algorithm based on a genetic optimization mechanism is proposed to achieve dynamic optimization seeking for parameters in local clustering to improve the clustering effect of local clustering. …”
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An improved synergistic dual-layer feature selection algorithm with two type classifier for efficient intrusion detection in IoT environment by G Logeswari, K Thangaramya, M Selvi, J. Deepika Roselind

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Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

“…To predict the VIV performance of a double-deck steel truss (DDST) girder with additional aerodynamic measures, the VIV response of a DDST bridge was investigated using wind tunnel tests and numerical simulation, a learning sample database was established with numerical simulation results, and a prediction model for the amplitude of the DDST girder and VIV parameters was established based on three machine learning algorithms. The optimization algorithm was selected using root mean square error (RMSE) and the coefficient of determination (R²) as evaluation indices and further improved with a genetic algorithm and particle swarm optimization. …”
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Evaluation Modeling of Electric Bus Interior Sound Quality Based on Two Improved XGBoost Algorithms Using GS and PSO by Enlai ZHANG, Yi CHEN, Liang SU, Ruoyu ZHONGLIAN, Xianyi CHEN, Shangfeng JIANG

“…Aiming at the practical application requirements of high-precision modeling of acoustic comfort in vehicles, this paper presented two improved extreme gradient boosting (XGBoost) algorithms based on grid search (GS) method and particle swarm optimization (PSO), respectively, with objective parameters and acoustic comfort as input and output variables, and established three regression models of standard XGBoost, GS-XGBoost, and PSO-XGBoost through data training. …”
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Denoising of electromagnetic data from different geological blocks using a hybrid PSO-GWO algorithm and CNN by Zhong-Yuan Liu, Zhong-Yuan Liu, Zhong-Yuan Liu, Di-Quan Li, Di-Quan Li, Di-Quan Li, Yecheng Liu, Yecheng Liu, Yecheng Liu, Xian Zhang, Xian Zhang, Xian Zhang

“…We propose a novel denoising approach that combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) to optimize a Convolutional Neural Network (CNN). …”
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TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables) by QI Junyan, CHE Yuhao, WANG Lei, YUAN Ruifu

“…During training, ISMA was used to iteratively optimize the learning rate of the TCN-LSTM-MHSA model to improve prediction accuracy and speed. Experimental results showed that: ① Compared with the Slime Mould Algorithm (SMA), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Sparrow Search Algorithm (SSA), the ISMA optimization strategy demonstrated better convergence speed and optimization ability in multiple benchmark function tests. ② In the stress prediction experiment, ablation experiments verified the necessity of TCN, LSTM, and MHSA modules. ③ The ISMA-optimized TCN-LSTM-MHSA model outperformed mainstream prediction models such as BP and GRU in MAE, RMSE, and R2 metrics, showing higher prediction accuracy and stability.…”
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A spherical vector-based adaptive evolutionary particle swarm optimization for UAV path planning under threat conditions by Yanfei Liu, Hao Zhang, Hao Zheng, Qi Li, Qi Tian

“…To address these challenges, we propose a spherical vector-based adaptive evolutionary particle swarm optimization (SAEPSO) algorithm. This algorithm, based on spherical vectors, directly incorporates UAV dynamic constraints and introduces improved tent map and reverse learning to enhance the diversity and distribution of initial solutions. …”
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