EEG channels selection for stroke patients rehabilitation using equilibrium optimizer by Al-Betar Mohammed Azmi, Alyasseri Zaid Abdi Alkareem, Makhadmeh Sharif Naser

“…This article addresses this problem by presenting an innovative optimization-based approach to the channel selection problem, employing a novel binary equilibrium optimizer (EO) as an optimization technique to identify the most relevant EEG channels. …”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

“…In addition, the second phase is named feature selection, and it is dependent on the Arithmetic Optimization Algorithm (AOA) being used to improve the Growth Optimizer (GO). …”
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Research of the Parameter Comprehensive Optimization of Excavator Working Device based on the Hybrid Optimization Algorithm by Zhang Xian, Liu Baixi, Qu Tao

“…The parameter of working device in the anti shovel hydraulic excavator are integrated optimized by using the hybrid algorithm of simulated annealing and penalty function. …”
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Study on the probabilistic characteristics of forces in the support structure of heliostat array based on the DBO-BP algorithm by Haiyin Luo, Qiwei Xiong, Xuewen Zhang, Shi Zuo

“…Dung beetle optimization (DBO) algorithm is a metaheuristic algorithm mimicking dung beetle ball-rolling behavior, while Back propagation (BP) neural network is a feedforward artificial neural network trained via error backpropagation to adjust parameters. …”
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An evolutionary-based optimization algorithm for truss sizing design by Pham Hoang Anh

“…Three truss sizing benchmark problems with discrete variables are used to examine the performance of the proposed algorithm. Objective functions of the optimization problems are minimum weights of the whole truss structures and constraints are stress in members and displacement at nodes. …”
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Multiplier leadership optimization algorithm (MLOA): unconstrained global optimization approach for melanoma classification by Sukanta Ghosh, Amar Singh, Shakti Kumar

“…Abstract This paper proposes the multiplier leadership optimization algorithm, which draws inspiration from multiplier leadership principles to search for and optimize solutions to complex problems effectively. …”
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Optimization of Jaw Crusher Based on Improved Genetic Algorithm by SUN Yu-fei, ZHENG Xiao-wen, CHEN Hao, LIU Xiao-Shan

“…Aiming at the deficiency of ANSYS′s own optimization algorithm, the improved genetic algorithm is applied to the structural optimization design of ANSYS.Taking the whole structure optimization of jaw crusher as an example, the optimization platform of jaw crusher based on SolidWorks and ANSYS is established.The traditional optimization algorithm of ANSYS and the improved genetic algorithm with embedded ANSYS finite element analysis are used to optimize the design.The results show that compared with the optimization algorithm of ANSYS, the improved genetic algorithm has obvious advantages in the overall structure design of jaw crusher. …”
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Optimal Placement of Phasor Measurement Unit in Electrical Grid Using Dingo Optimization Algorithm by ARIYO Funso Kehinde, AYANLADE Samson Oladayo, JIMOH Abdulrasaq, ADEBAYO Moses Taiwo

“…The study utilizes the Dingo Optimization Algorithm, a metaheuristic inspired by nature, to identify the best PMU placement. …”
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A new human-based offensive defensive optimization algorithm for solving optimization problems by Ning Fang, Cheng Xu, Xuxiong Gong, Zhouhua Wu

“…Abstract A novel human-inspired metaheuristic algorithm, termed Offensive Defensive Optimization, has been introduced to address single-objective optimization problems. …”
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Comparative Review of Multi-Objective Optimization Algorithms for Design and Safety Optimization in Electric Vehicles by I Gede S. S. Dharma, Rachman Setiawan

“…Despite the widespread use of established optimization algorithms like Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), Non-Dominated Sorting Genetic Algorithm-III (NSGA-III), and Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D) in real-world engineering optimization problems, newer algorithms such as Two-Stage NSGA-II (TS-NSGA-II), Dynamic Constrained NSGA-III (DCNSGA-III), MOEA/D with Virtual Objective Vectors (MOEA/D-VOV), Large-Scale Evolutionary Multi-Objective Optimization Assisted by Directed Sampling (LMOEA-DS), and Super-Large-Scale Multi-Objective Evolutionary Algorithm (SLMEA) remain underexplored in the context of Battery Electric Vehicle (BEV) safety, particularly in optimizing complex, non-linear, and constrained multi-objective problems like crashworthiness and thermal management. …”
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Polar lights optimizer: A novel algorithm for accurate parameter estimation in proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Ali Fayez Alkoradees, Mohammad Khishe, Reena Jangid

“…The PLO algorithm generates SSE results of 0.025493 for BCS 500 W and 0.275211 for Nedstack 600 W PS6 and 0.283774 for STD 250 W Stack while keeping AE at 0.259293 and RE% at 1.185075 for the STD 250 W Stack. …”
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Portfolio Optimization with Artificial Hummingbird Algorithm for Cement Industry by Murat Erhan Çimen

“…Portfolio optimization, which is performed while investing in any asset, is an important issue for all investors and finance researchers. …”
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An optimal L∞-PLA algorithm for trajectory data compression by ZHAO Huanyu, SUN Guohao, LI Tongliang, YANG Jian, PANG Chaoyi

“…MDisPLA used a divide-and-conquer strategy to extend the one-dimensional optimal PLA algorithm for optimizing compression of multi-dimensional trajectory data. …”
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Multi-strategy collaborative optimization of gravitational search algorithm by Zhonghua Yang, Yuanli Cai, Ge Li, Peng Wang, Yu Chen

“…In the early iterations, particle positions are primarily updated using the original gravitational force, preserving the inherent characteristics of the gravitational search algorithm. In the later stages, particles with better fitness values are updated using a globally optimal Lévy random walk strategy to enhance local search capabilities, while particles with poorer fitness values are updated using the sparrow algorithm follower strategy. …”
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Fast autoscaling algorithm for cost optimization of container clusters by José María López, Joaquín Entrialgo, Manuel García, Javier García, José Luis Díaz, Rubén Usamentiaga

“…In comparison to the heuristics, FCMA achieves similar solving times while consistently delivering more cost-effective solutions.…”
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Optimization of the Weight Processing Algorithm in Multichannel Doppler Filtering by V. I. Koshelev, Ngoc Hieu Trinh

“…An MDF synthesis was carried out using optimization procedures, and the effectiveness of the algorithms was assessed using computer calculations.Results. …”
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Evolving the Whale Optimization Algorithm: The Development and Analysis of MISWOA by Chunfang Li, Yuqi Yao, Mingyi Jiang, Xinming Zhang, Linsen Song, Yiwen Zhang, Baoyan Zhao, Jingru Liu, Zhenglei Yu, Xinyang Du, Shouxin Ruan

“…This paper introduces an enhanced Whale Optimization Algorithm, named the Multi-Swarm Improved Spiral Whale Optimization Algorithm (MISWOA), designed to address the shortcomings of the traditional Whale Optimization Algorithm (WOA) in terms of global search capability and convergence velocity. …”
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Multiple strategy enhanced hybrid algorithm BAGWO combining beetle antennae search and grey wolf optimizer for global optimization by Fan Zhang, Chuankai Liu, Peng Liu, Shuiting Ding, Tian Qiu, Jiajun Wang, Huipeng Du

“…Abstract This study proposes BAGWO, a novel hybrid optimization algorithm that integrates the Beetle Antennae Search algorithm (BAS) and the Grey Wolf Optimizer (GWO) to leverage their complementary strengths while enhancing their original strategies. …”
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Slope stability prediction under seismic loading based on the EO-LightGBM algorithm by Ning Ma, Ning Ma, Yuqi Zhang, Zaizhen Yao

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Mixed Multi-Strategy Improved Aquila Optimizer and Its Application in Path Planning by Tianyue Bao, Jiaxin Zhao, Yanchang Liu, Xusheng Guo, Tianshuo Chen

“…Traditional Aquila Optimizers, while effective, face limitations such as uneven population initialization, a tendency to get trapped in local optima, and slow convergence rates. …”
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