Nature-inspired MPPT algorithms for solar PV and fault classification using deep learning techniques by S. Senthilkumar, V. Mohan, S. P. Mangaiyarkarasi, R. Gandhi Raj, K. Kalaivani, N. Kopperundevi, M. Chinnadurai, M. Nuthal Srinivasan, L. Ramachandran

“…To select the best optimization model for MPPT under PSC, the nature-inspired dragonfly algorithm (DA), moth flame optimization algorithm (MFOA), grasshopper optimization algorithm (GOA), and salp swarm optimization algorithm (SSOA) are used in this work to evaluate the tracking efficiency (TE) of the solar PV systems. …”
Get full text

Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

“…This work employs single hidden layer extreme learning machine (ELM) algorithm and hybrid particle swarm optimization-based support vector regression (PS-SVR) for determining energy storage efficiency of high-entropy ceramics. …”
Get full text

Continuously Variable Geometry Quadrotor: Robust Control via PSO-Optimized Sliding Mode Control by Foad Hamzeh, Siavash Fathollahi Dehkordi, Alireza Naeimifard, Afshin Abyaz

“…A sliding mode control algorithm, optimized using particle swarm optimization, is implemented to ensure stability and high performance in the presence of uncertainties and noise. …”
Get full text

Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…In this paper, these described limitations are addressed through the introduction of an integrated approach that couples predictive Life Cycle Assessment (LCA) with Gaussian Process Regression (GPR), dynamic decision criteria weighting via Stochastic Forest for Multi-Criteria Decision Analysis (MCDA), and multi-objective optimization using Particle Swarm Optimization (PSO). …”
Get full text

Optimal power flow using recent red-tailed hawk optimization algorithm by Ahmed M Nassef, Mohammad Ali Abdelkareem, Mohamed Louzazni

“…In addition, the results obtained from the suggested approach have been compared to those achieved by other modern and competitive metaheuristic optimization algorithms, such as particle swarm optimization (PSO), Coot bird's algorithm (COOT), salp swarm algorithm (SSA), Marin predator algorithm (MPA), and the jellyfish search optimizer (JSO). …”
Get full text

Research on Performance Predictive Model and Parameter Optimization of Pneumatic Drum Seed Metering Device Based on Backpropagation Neural Network by Yilong Pan, Yaxin Yu, Junwei Zhou, Wenbing Qin, Qiang Wang, Yinghao Wang

“…The method applies a backpropagation neural network (BPNN) to establish a predictive model and multi-objective particle swarm optimization (MOPSO) to search for the optimal solution. …”
Get full text

Control-Oriented Real-Time Trajectory Planning for Heterogeneous UAV Formations by Weichen Qian, Wenjun Yi, Shusen Yuan, Jun Guan

“…Inspired by Model Predictive Control (MPC), in the trajectory planning stage, the method generates multi-step trajectory points using an improved artificial potential field (APF) method, estimates the actual formation trajectory using the prediction network, and optimizes the trajectory through a multi-objective particle swarm optimization (MOPSO) algorithm after evaluating the planning costs. …”
Get full text

Towards a Digital Twin for Gas Turbines: Thermodynamic Modeling, Critical Parameter Estimation, and Performance Optimization Using PINN and PSO by Jian Tiong Lim, Achnaf Habibullah, Eddie Yin Kwee Ng

“…The developed ANNs are then combined with particle swarm optimization (PSO) to carry out performance optimization in real time. …”
Get full text

Multiobjective Time-Space Grid Optimization of Lithium-Ion Electrochemical Model Based on Stability Analysis and Limit Region Decoupling Strategy by Libin Zhang, Minghang Zhang, Hongying Shan, Guan Xu, Jingsheng Dong, Xuemeng Bai

Get full text

A multi objective optimization framework for smart parking using digital twin pareto front MDP and PSO for smart cities by Dinesh Sahu, Priyanshu Sinha, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Lu Wang

“…In response to these challenges, this paper proposes a Multi-Objective Optimization Framework for Smart Parking incorporating Digital Twin Technology, Pareto Front Optimization, Markov Decision Process (MDP), and Particle Swarm Optimization (PSO). …”
Get full text

Evaluation of the effects of the body on athletes’ emotions and motivational behaviors from the perspective of big data public health by Qiang Zhang, Diandong Lian, Yiqiao Zhang

“…ObjectiveAn analysis was conducted on the impact of the body on athletes’ emotions and motivation from the perspective of Public Health (PH).MethodsPSO-KNN (Particle Swarm Optimization-K-Nearest Neighbor) algorithm and PSO-SVM algorithm (Particle Swarm Optimization-Support Vector Machine) were obtained by combining Particle Swarm Optimization (PSO), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM), and then the recognition rates of the two algorithms were compared.ResultsWhen comparing the PSO-KNN algorithm and PSO-SVM algorithm on baseline removed and baseline not removed, the average recognition rates of PSO-KNN algorithm and PSO-SVM algorithm under emotional state were 56.66 and 54.75%, respectively. …”
Get full text

Security-Enhanced Image Encryption: Combination of S-Boxes and Hyperchaotic Integrated Systems by Renjie Song, Haixia Zhao

“…In this paper, an image encryption method combining S-box and hyperchaotic integrated system is proposed. First, a particle swarm optimization algorithm is designed to search for S-boxes based on an adaptive function that takes into account several security metrics and an S-function inertia weighting strategy. …”
Get full text

Stochastic robot failure management in an assembly line under industry 4.0 environment by Kuldip Singh Sangwan, Anirudh Tusnial, Suveg V Iyer

“…This paper proposes an improved integrated model of operation reallocation and robot allocation for stochastic failures of a robotic assembly line. A particle swarm optimization (PSO) algorithm is developed to solve the proposed integrated model. …”
Get full text

Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…To solve the problem of high cost and low efficiency of measuring equipment in traditional distribution network fault location, a fault section location and line selection strategy combining dynamic binary particle swarm optimization (DBPSO) configuration and fuzzy C-means (FCM) clustering is proposed in this paper. …”
Get full text

RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…The RL-QPSO Net combines quantum-inspired particle swarm optimization (QPSO) and deep reinforcement learning (DRL) modules through a dual control mechanism to achieve path optimization and environmental adaptation. …”
Get full text

A Combined PSO-LSTM Prediction Model for Dam Deformation by HAO Ze-jia, SHI Yu-qun, CHENG Bo-chao, HE Jin-ping

“…By leveraging the long-short-term memory (LSTM) model and particle swarm optimization (PSO) algorithm from artificial intelligence technology, a combined PSO-LSTM dam deformation prediction model is established, offering a novel approach for enhancing the accuracy of dam deformation prediction. …”
Get full text

Communication‐awareness adaptive resource scheduling strategy for multiple target tracking in a multiple radar system by Yang Su, Ziyang Cheng, Zishu He, Minglong Deng

“…To tackle the resultant mixed‐integer, non‐convex, and non‐linear problem efficiently, incorporating with the proposed hybrid particle swarm optimization algorithm based on the Kullback–Leibler divergence, a two‐stage solution technique is developed to obtain the near‐optimal solution. …”
Get full text

A deep learning-based hybrid method for PM2.5 prediction in central and western China by Zuhan Liu, Zihai Fang, Yuanhao Hu

“…The model integrates the transformer and LSTM architectures and employs parameter optimization through the particle swarm optimization (PSO) algorithm. …”
Get full text

Fault Location Method for Communication Link with Multi-information Fusion Modeling of Smart Substation by Zhiyong PI, Yi ZHU, Xuan LIAO, Zhenxing LI, Hao FANG, Pei WU

Get full text

Integrated DDPG-PSO energy management systems for enhanced battery cycling and efficient grid utilization by Oladimeji Ibrahim, Mohd Junaidi Abdul Aziz, Razman Ayop, Wen Yao Low, Nor Zaihar Yahaya, Ahmed Tijjani Dahiru, Temitope Ibrahim Amosa, Shehu Lukman Ayinla

“…Effective energy management is crucial in hybrid energy systems for optimal resource utilization and cost savings. This study integrates Deep Deterministic Policy Gradient (DDPG) with Particle Swarm Optimization (PSO) to enhance exploration and exploitation in the optimization process, aiming to improve energy resource utilization and reduce costs in hybrid energy systems. …”
Get full text