Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Furthermore, low-level optimization techniques like genetic algorithms as well as particle swarm optimization are used to fine tune the specific model parameters and to reduce the computational overhead for improving the detection efficacy still more. …”
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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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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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Harris Hawks Optimization for Soil Water Content Estimation in Ground-Penetrating Radar Waveform Inversion by Hanqing Qiao, Minghe Zhang, Maksim Bano

“…To further validate our approach, the results of the HHO algorithm are also compared with those of partial swarm optimization (PSO) and grey wolf optimizer (GWO). …”
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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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A New Computer-Aided Diagnosis System for Breast Cancer Detection from Thermograms Using Metaheuristic Algorithms and Explainable AI by Hanane Dihmani, Abdelmajid Bousselham, Omar Bouattane

“…To achieve these goals, we proposed a new multi-objective optimization approach named the Hybrid Particle Swarm Optimization algorithm (HPSO) and Hybrid Spider Monkey Optimization algorithm (HSMO). …”
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Multi-Objective Optimization of Three-Stage Turbomachine Rotor Based on Complex Transfer Matrix Method by Hüseyin Tarık Niş, Ahmet Yıldız

“…This study presents the complex transfer matrix method (CTMM) as an advanced mathematical model, providing significant advantages over the finite element method (FEM) by yielding rapid solutions for complex optimization problems. In order to design a more efficient structure of a three-stage turbomachine rotor, we integrated this method with various optimization algorithms, including genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), gravitational search algorithm (GSA), black hole (BH), particle swarm optimization (PSO), Harris hawk optimization (HHO), artificial bee colony (ABC), and non-metaheuristic pattern search (PS). …”
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Deep reinforcement learning-based resource joint optimization for millimeter-wave massive MIMO systems by LIU Qingli, LI Xiaoyu, LI Rui

“…Experimental results show that the proposed joint optimization method significantly improves the throughput and energy efficiency of the system compared with the single-stage all-digital precoding and hybrid precoding equal resource allocation methods and the particle swarm optimization-based resource allocation algorithm.…”
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Optimal Adaptive Robust Pitch Control with Load Mitigation for Uncertain Variable Speed Wind Turbines by Sara Majidi, Reza Shahnazi

“…It is proved that the closed-loop signals are semi-globally uniformed and ultimately bounded. The optimal parameters of the proposed controller are derived by solving a proposed multi-objective optimization problem using non-dominated sorting genetic algorithm-II (NSGA-II) and multi-objective particle swarm optimization (MOPSO) algorithm. …”
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Optimization Strategy for Building Electrical Devices Considering Multi-Comfort and Economic Virtual Game Players by Xiyong Bao, Zhen Feng, Qiao Yan, Ruiqi Wang

“…Finally, the optimization strategy is solved by using a particle swarm optimization algorithm. …”
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Combined Dynamic Route Guidance and Signal Timing Optimization for Urban Traffic Congestion Caused by Accidents by He Zhang, Shanshan Guo, Xuzhi Long, Yuanyuan Hao

“…This model is solved with a particle swarm optimization algorithm and simulated to the actual road network with VISSIM. …”
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A node deployment and resource optimization method for CPDS based on cloud‐fog‐edge collaboration by Xiaoping Xiong, Geng Yang

“…Subsequently, an improved multi‐objective particle swarm optimization algorithm (MWM‐MOPSO) is employed to solve the task resource allocation problem. …”
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Integration of Distributed Energy Resources in Unbalanced Networks Using a Generalized Normal Distribution Optimizer by Laura Sofía Avellaneda-Gómez, Brandon Cortés-Caicedo, Oscar Danilo Montoya, Jesús M. López-Lezama

“…The proposed approach is tested on 25- and 37-node feeders and benchmarked against three widely used metaheuristic algorithms: the Chu and Beasley Genetic Algorithm, Particle Swarm Optimization, and Vortex Search Algorithm. …”
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Hybrid multi-objective optimization of µ-synthesis robust controller for frequency regulation in isolated microgrids by Abdallah Mohammed, Ahmed Kadry, Maged Abo-Adma, Adel El Samahy, Rasha Elazab

“…The controller is optimized using multi-objective particle swarm optimization (MOPSO) and multi-objective genetic algorithm (MOGA) under inequality constraints, employing a Pareto front to identify optimal solutions. …”
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Optimal Decision-making Method of Wind-proof and Disaster-resistant Reinforcement Measures for Distribution Network by Xin GAO, Fei TANG, Tongyan ZHANG, Yu LI

“…The reinforcement strategy was further optimized through the particle swarm optimization algorithm, considering the total reinforcement budget, the load importance and the component fragility. …”
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