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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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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3D Pattern Synthesis of Time-Modulated Conformal Arrays with a Multiobjective Optimization Approach by Wentao Li, Yongqiang Hei, Jing Yang, Xiaowei Shi

“…The multiobjective particle swarm optimization (MOPSO) is applied to optimize the switch-on instants and pulse durations of the time-modulated conformal array. …”
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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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Extending WSN Lifetime with Enhanced LEACH Protocol in Autonomous Vehicle Using Improved K-Means and Advanced Cluster Configuration Algorithms by Cheolhee Yoon, Seongsoo Cho, Yeonwoo Lee

“…The simulation results demonstrate that the proposed approach improves performance in terms of the first node dead (FND) and 80% alive nodes metrics with mobility, compared to other LEACH protocols such as classical LEACH, LEACH-B, Improved-LEACH, LEACH with K-means, Particle Swarm Optimization (PSO), and LEACH-GK protocol, thereby enhancing network lifetime through optimal CH selection.…”
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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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Jointly Optimizing Resource Allocation, User Scheduling, and Grouping in SBMA Networks: A PSO Approach by Jianjian Wu, Chanzi Liu, Xindi Wang, Chi-Tsun Cheng, Qingfeng Zhou

“…To tackle this NP-hard problem, we propose an effective algorithm based on Particle Swarm Optimization (PSO), featuring a carefully designed update function tailored specifically for the joint US and UG decisions required in SBMA. …”
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…The framework uses an enhanced particle swarm optimization (PSO) algorithm to reconcile competing goals, including maintaining operator safety, optimizing asset reliability, and minimizing maintenance costs. …”
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Optimizing enhanced coalbed methane recovery in thick lignite formations: An integrated technical and economic evaluation by Zhiming Fang, Shaicheng Shen

“…We evaluate the economic feasibility of ECBM under various gas injection scenarios and optimize key operational parameters through a coupled neural network model and particle swarm optimization algorithm. …”
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Analysis of Performance of SSSC FACTS Device Using PSO Based Optimal Power Flow Solutions by Smt Padma, Kanchapogu Vaisakh

“…The particle swarm optimization is used for solving the optimal power flow problem for steady-state studies. …”
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Multi-Objective Parameter Optimization of Electro-Hydraulic Energy-Regenerative Suspension Systems for Urban Buses by Zhilin Jin, Xinyu Li, Shilong Cao

“…To streamline multi-objective optimization processes, a particle swarm optimization–back propagation (PSO-BP) neural network surrogate model was developed to approximate the complex co-simulation system. …”
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Research on the Operation Optimization of Public Building Systems in Extremely Cold Areas Based on Flexible Loads by Chuan Tian, Shunli Jiang, Shuai Li, Guohui Feng, Bin Yu

“…A two-stage operation optimization method is proposed: the first stage simulates the starting and stopping control conditions of equipment at varying temperatures and times, selecting the optimal time period to regulate the thermal loads; the second stage employs a multi-objective particle swarm optimization algorithm to optimize the scheduling of the system’s electrical load. …”
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