A Hybrid Multi-Strategy Optimization Metaheuristic Algorithm for Multi-Level Thresholding Color Image Segmentation by Amir Seyyedabbasi

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An effective feature selection approach based on hybrid Grey Wolf Optimizer and Genetic Algorithm for hyperspectral image by Yiqun Shang, Minrui Zheng, Jiayang Li, Xinqi Zheng

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Exploration Enhanced RPSO for Collaborative Multitarget Searching of Robotic Swarms by Jian Yang, Ruilin Xiong, Xinhao Xiang, Yuhui Shi

“…Particle Swarm Optimization (PSO) is an excellent population-based optimization algorithm. …”
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Towards efficient image segmentation: A fuzzy entropy-based approach using the snake optimizer algorithm by A. Tamilarasan, D. Rajamani

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An Intelligently Enhanced Ant Colony Optimization Algorithm for Global Path Planning of Mobile Robots in Engineering Applications by Peng Li, Lei Wei, Dongsu Wu

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Inverse design of nanophotonic devices enabled by optimization algorithms and deep learning: recent achievements and future prospects by Kim Junhyeong, Kim Jae-Yong, Kim Jungmin, Hyeong Yun, Neseli Berkay, You Jong-Bum, Shim Joonsup, Shin Jonghwa, Park Hyo-Hoon, Kurt Hamza

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RESEARCH ON ROLLING BEARING FAULT DIAGNOSIS BASED ON MA OPTIMIZATION OF CNN by TIAN LiYong, ZHAO JianJun, YU Ning

“…Aiming at the high dependence of super parameter selection on artificial experience in rolling bearing state identification based on convolution neural network(CNN),a fault diagnosis model(CNN⁃MA)based on mayfly algorithm(MA)was proposed.Firstly,the model used the powerful optimization ability of MA,took the diagnostic accuracy of CNN as the optimization objective,and adaptively adjusted the super parameters in CNN.Secondly,the normalized original signal image set was used to preserve the characteristics of the signal as much as possible.Finally,in order to evaluate the effectiveness of the parameters in the optimization model,compared with the CNN model optimized by particle swarm optimization(PSO)algorithm.The results show that the proposed model has more stable performance,higher recognition accuracy and good anti⁃noise ability.It fully shows the feasibility and reliability of CNN⁃MA model in fault diagnosis of rolling bearings.…”
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Programming UAV swarm operational test based on mission reliability by WANG Jingyu, JIANG Ping, XIE Dingxing, QI Jianjun

“…Then, using the multi-objective quantum particle swarm optimization algorithm, the Pareto boundary is solved and the optimal program that comprehensively considers reliability and cost is determined. …”
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Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…By integrating self-conducted experimental data and referenced datasets, a diverse experimental database was constructed. Improved algorithms, namely Asynchronous Learning Particle Swarm Optimization (AsyLnCPSO) and Hybrid Genetic Algorithm-based Particle Swarm Optimization (GA-HIDMS-PSO), were paired with LSTM neural networks to systematically evaluate their adaptability and effectiveness in predicting the performance of basalt fiber-reinforced concrete under freeze-thaw conditions. …”
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Direct methanol fuel cells parameter identification with enhanced algorithmic technique by Manish Kumar Singla, Muhammed Ali S.A, Ramesh Kumar, Hamed Zeinoddini-Meymand, Farhad Shahnia

“…A number of optimization techniques have been adopted: Particle Swarm Optimization (PSO), Dragonfly Algorithm (DA), Harris Hawk Optimizer (HHO), Rhinoceros Search Algorithm (RSA), Artificial Hummingbird Algorithm (AHA), and its enhanced version, Enhanced artificial hummingbird algorithm (EAHA). …”
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Optimization of a photovoltaic/wind/battery energy-based microgrid in distribution network using machine learning and fuzzy multi-objective improved Kepler optimizer algorithms by Fude Duan, Mahdiyeh Eslami, Mohammad Khajehzadeh, Ali Basem, Dheyaa J. Jasim, Sivaprakasam Palani

“…Also, the MOIKOA superior capability is validated in comparison with the multi-objective conventional Kepler optimization algorithm, multi-objective particle swarm optimization, and multi-objective genetic algorithm in problem-solving. …”
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Bias-Reduced Localization for Drone Swarm Based on Sensor Selection by Bo Wu, Bazhong Shen, Yonggan Zhang, Li Yang, Zhiguo Wang

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A UAV path planning algorithm for bridge construction safety inspection in complex terrain by Wenyuan Xu, Chuang Cui, Yongcheng Ji, Xiang Li, Shuai Li

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Intelligent resource scheduling scheme for UAV swarm collaborative sensing by ZHAO Pengcheng, LI Tianyang, LENG Supeng, XIONG Kai

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Mcaaco: a multi-objective strategy heuristic search algorithm for solving capacitated vehicle routing problems by Yanling Chen, Jingyi Wei, Tao Luo, Jie Zhou

“…Through a series of experiments, it is demonstrated that compared to multi-objective particle swarm optimization (MOPSO), non-dominated sorting genetic algorithm II (NSGA-II), and multi-objective sparrow search algorithm (MOSSA), the proposed MCAACO significantly reduces travel paths by an average of 3.05% and increases vehicle service coverage by an average of 3.2%, while satisfying vehicle capacity constraints. …”
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Hybrid Improved PSO Algorithm for Soil Property Parameter Estimation by Mude Li, Aiping Shi, Yefan Shi, Tao Zhang, Cu Qu, Lihua Ye

“…This study proposes a hybrid PSO-EDO algorithm, integrating Particle Swarm Optimization (PSO) and the Exponential Distribution Optimizer (EDO) for efficient and accurate estimation of soil property parameters. …”
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An Elegant Multi-Agent Gradient Descent for Effective Optimization in Neural Network Training and Beyond by Mohammad Sakka, Mohammad Reza Bahrami

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A Survey of Nature-Inspired Meta-Heuristic Algorithms in Network Alignment by Anagh Awal, Farsuram Pandit

“…This paper offers a thorough examination of the application of these meta-heuristic algorithms to network alignment. It explores a wide range of nature-inspired algorithms, including genetic algorithms, particle swarm optimization, ant colony optimization, and simulated annealing. …”
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Techno-Economic Feasibility Analysis of Hybrid Renewable Energy System By Using Particle Optimization Technique for the Rural Border Areas in Iraq : Case Study by Husam Salim, Jabbar Rashed

“…This study made use of the MATLAB-based three different types of Particle Swarm Optimization algorithms(PSO),namely,(Modified PSO, Canonical-PSO and Hierarchical PSO with Time-varying Acceleration Coefficients (HPSO-TVAC) When designing a HES, it is important to strike a balance between the three goals of Cost Of Energy (COE), Reliability (REL), and maximizing the value of Renewable Energy Penetration (REP). …”
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A modified perturb and observe MPPT algorithm for PEMFC with rapid convergence and low power oscillation by Resat Celikel, Omur Aydogmus, Musa Yilmaz

“…A comparative analysis is conducted against the conventional P&O and optimization-based MPPT algorithms, including Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), and Genetic Algorithm (GA). …”
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