Impedance Characteristic-Based Frequency-Domain Parameter Identification Method for Photovoltaic Controllers by Yujia Tang, Xin Zhou, Yihua Zhu, Junzhen Peng, Chao Luo, Li Zhang, Jinling Qi

“…A frequency-segmented parameter identification method is introduced, capable of fast convergence without relying on a specific optimization algorithm. Finally, the proposed method’s identification results are compared with actual values, voltage ride-through-based identification, particle swarm optimization results, and results under uncertain conditions. …”
Get full text

Implementation of a low-cost current perturbation-based improved PO MPPT approach using Arduino board for photovoltaic systems by Abdelkhalek Chellakhi, Said El Beid, Mouncef El Marghichi, El Mahdi Bouabdalli, Ambe Harrison, Hassan Abouobaida

“…To evaluate the effectiveness of the proposed technique, comparative analyses are conducted against the traditional PO algorithm, particle swarm optimization (PSO), fuzzy logic control (FLC), and a recently introduced approach, the zone voltage (ZV) method. …”
Get full text

A Study on Path Planning for Curved Surface UV Printing Robots Based on Reinforcement Learning by Jie Liu, Xianxin Lin, Chengqiang Huang, Zelong Cai, Zhenyong Liu, Minsheng Chen, Zhicong Li

“…Experimental results show that the proposed method outperforms traditional path planning methods, as well as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). …”
Get full text

Meteorological data implications modeling on evapotranspiration variability in arid and semi-arid zones in Saudi Arabia using hybrid metaheuristic by Oulad Naoui Noureddine, Sekkoum Mohamed, Cherif El Amine, Ali Alzaed, Meseret Abeje Gedfew, Sherif S. M. Ghoneim, Enas E. Hussein

Get full text

Synergistic effect of artificial intelligence and new real-time disassembly sensors: Overcoming limitations and expanding application scope by Bozhou Li, Dajiang Ju, Xingwang Li, Yan Liu, Hongru He, Hao Wang

“…Then, based on the gated recurrent unit (GRU) model, the article applied the particle swarm optimization (PSO) algorithm to optimize the parameters of the GRU network and used the support vector machine (SVM) model to optimize the classification function of the network output. …”
Get full text

A Simple Method for Correcting Empirical Model Densities During Geomagnetic Storms Using Satellite Orbit Data by Daniel A. Brandt, Charles D. Bussy‐Virat, Aaron J. Ridley

Get full text

Establishment of Hyperspectral Prediction Model of Water Content in Anshan-Type Magnetite by Xiaoxiao XIE, Yang BAI, Jiuling ZHANG, Yuna JIA

“…In order to further improve the prediction ability of the model, the competitive adaptive reweighting method (CARS) was used to optimize the characteristic band, and a prediction model was established by combining random forest regression (RFR), least squares support vector regression (LSSVR) and particle swarm optimization least squares support vector regression (PSO-LSSVR). …”
Get full text

Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

“…A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. …”
Get full text

Improving agricultural commodity allocation and market regulation: a novel hybrid model based on dual decomposition and enhanced BiLSTM for price prediction by Lihua Zhang, Fushun Wang, Fushun Wang, Kejian Wang, Kejian Wang, Zhenxue He, Zhenxue He, Chen Chen, Chen Chen, Jiahao Liu, Jiahao Liu, Chao Wang, Chao Wang, Zhe Wang

“…This paper proposes a sustainable hybrid model SV-PSO-BiLSTM which integrates Seasonal-Trend decomposition procedure based on Loess (STL), Variational Mode Decomposition (VMD), Particle Swarm Optimization (PSO), and Bidirectional Long Short-Term Memory (BiLSTM) neural networks. …”
Get full text

Digital Twin Driven Four-Dimensional Path Planning of Collaborative Robots for Assembly Tasks in Industry 5.0 by Ilias Chouridis, Gabriel Mansour, Asterios Chouridis, Vasileios Papageorgiou, Michel Theodor Mansour, Apostolos Tsagaris

Get full text

A multi-objective metaheuristic method for node placement in dynamic IoT environments by Farzad Kiani

Get full text

Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network by Wenbang Zhu, Yuhang Li, Xiumei Zheng, Enze Hao, Dali Zhang, Zhen Wang

“…To precisely obtain DSGM exhibiting exceptional mechanical properties, the Backpropagation Neural Network (BPNN) model was optimized through the utilization of Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), and Genetic Algorithm (GA). …”
Get full text

A Predictive Method for Greenhouse Soil Pore Water Electrical Conductivity Based on Multi-Model Fusion and Variable Weight Combination by Jiawei Zhao, Peng Tian, Jihong Sun, Xinrui Wang, Changjun Deng, Yunlei Yang, Haokai Zhang, Ye Qian

“…We propose a hybrid prediction model—PSO–CNN–LSTM–BOA–XGBoost (PCLBX)—that integrates a particle swarm optimization (PSO)-enhanced convolutional LSTM (CNN–LSTM) with a Bayesian optimization algorithm-tuned XGBoost (BOA–XGBoost). …”
Get full text

Berth Allocation and Quay Crane Assignment Considering the Uncertain Maintenance Requirements by Siwei Li, Liying Song

Get full text

Integrated intrusion detection design with discretion of leading agent using machine learning for efficient MANET system by K. S. Nirmala Bai, Dr M.V. Subramanyam

“…Particle Swarm Optimization (PSO) is defined for the initial clustering of nodes and immediately the O-MLM is performed to detect the leading agent nodes in each cluster with the selection features of node degree, node mobility, energy, distance and delay. …”
Get full text

Analysis of the Trends and Driving Factors of Cultivated Land Utilization Efficiency in Henan Province from 2000 to 2020 by Henggang Zhang, Chenhui Zhu, Tianyu Jiao, Kaiyue Luo, Xu Ma, Mingyu Wang

“…Additionally, we used a genetic algorithm optimized Artificial Neural Network (ANN) and a particle swarm optimization-based Random Forest (RF) model to assess the comprehensive in-fluence between topography, climate, and human activities on CLUE, in which incorporating Shapley Additive Explanations (SHAP) values. …”
Get full text

Comparative Evaluation of Fractional-Order Models for Lithium-Ion Batteries Response to Novel Drive Cycle Dataset by Xinyuan Wei, Longxing Wu, Chunhui Liu, Zhiyuan Si, Xing Shu, Heng Li

“…First, three typical FOMs were initially established and the particle swarm optimization algorithm was then employed to identify model parameters. …”
Get full text

InBRwSANet: Self-attention based parallel inverted residual bottleneck architecture for human action recognition in smart cities. by Yasir Khan Jadoon, Muhammad Attique Khan, Yasir Noman Khalid, Jamel Baili, Nebojsa Bacanin, MinKyung Hong, Yunyoung Nam

“…The proposed architecture is trained on the selected datasets, whereas the hyperparameters are chosen using the particle swarm optimization (PSO) algorithm. The trained model is employed in the testing phase for the feature extraction from the self-attention layer and passed to the shallow wide neural network classifier for the final classification. …”
Get full text

Neural network backstepping control of OWC wave energy system by Priyanka Nath, Sunil Kumar Mishra, Amitkumar Vidyakant Jha, Bhargav Appasani, Akshaya Kumar Pati, Vijay Kumar Verma, Philibert Nsengiyumva, Avireni Srinivasulu

“…The parameters for PI, BSC, and NN-BSC are optimized using a Particle Swarm Optimization (PSO) algorithm, which minimizes a fitness function defined by the Integral Squared Error (ISE). …”
Get full text

A multistate transition model for survival estimation in randomized trials with treatment switching and a cured subgroup by Haixia Hu, Ling Wang, Kejian Wu, Wei Ge, Jielai Xia, Chen Li

“…Meanwhile, the semi-competing risks model is used for the treatment effect evaluation on the uncured patients through transitional hazards between states of PD, treatment switching, and death. The particle swarm optimization algorithm is employed to estimate the model parameters. …”
Get full text