Rock image classification based on improved EfficientNet by Kai Bai, Zhaoshuo Zhang, Siyi Jin, Shengsheng Dai

“…Second, the shuffle attention mechanism is integrated into the backbone network to enhance feature extraction while reducing model parameters. Finally, the Lion optimizer is employed to optimize the training process, improving both the accuracy and stability of the model. …”
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Capacity optimization strategy for gravity energy storage stations considering the impact of new power systems. by Can Lv, Jun He, Jingjing Ma, Yukun Yang, Fan Liu, Wentao Huang

“…The model is solved using an enhanced Grasshopper Optimization Algorithm (W-GOA) incorporating a whale spiral motion strategy to improve convergence and solution accuracy. …”
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Rolling optimization method of virtual power plant demand response based on Bayesian Stackelberg game by Binxi Huang

“…This is iteratively solved using the whale algorithm to determine the optimal power generation distribution scheme for each unit on both the supply side and demand sides. …”
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Unveiling global flood hotspots: Optimized machine learning techniques for enhanced flood susceptibility modeling by Mahdi Panahi, Khabat Khosravi, Fatemeh Rezaie, Zahra Kalantari, Jeong-A. Lee

“…This study assessed the efficiency of three machine learning approaches, including support vector regression (SVR) and its optimized versions through combination with grey wolf optimizer (GWO) and whale optimization algorithm (WOA), in generating accurate flood susceptibility maps at a global scale. …”
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Optimal nodes selection in wireless sensor and actor networks based on prioritized mutual exclusion approach by VIRENDER RANGA, Mayank Dave, Anil K. Verma

“…We have proposed two algorithms, centralizedprioritized h-out-of-k mutual exclusion algorithm (CPMEA), and distributed prioritizedh-out-of-k mutual exclusion algorithm (DPMEA) in this research paper. …”
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Fast and Accurate Direct Position Estimation Using Low-Complexity Correlation and Swarm Intelligence Optimization by Yuze Duan, Zuping Tang, Jiaolong Wei, Jie Sun, Kaixian Ying

“…Furthermore, an adaptive Dung Beetle Optimization (ADBO) algorithm is developed. By leveraging insights from fitness landscape analysis, the ADBO algorithm dynamically adjusts subpopulation proportions and the convergence factor while incorporating hybrid mutation strategies for effective adaptation to various types of optimization problems. …”
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A mechanism of topology optimization for underwater acoustic sensor networks based on autonomous underwater vehicles by Ming He, Fangxin Liu, Zhuang Miao, Huan Zhou, Qiuli Chen

“…To solve this problem, a topology optimization method, also called TO-A algorithm, is developed based on topology reconfiguration. …”
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Precise motion control for a space mining robot based on improved African vultures optimization by Baiyi Wang, Xinhua Liu, Marek Rydel, Dezheng Hua, Rafal Stanislawski, Hui Wang, Ke Feng, Zhixiong Li

“…Then, the optimal PID motion controller is developed based on the improved African vultures optimization algorithm (IAVOA). …”
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Optimization of Processor Clock Frequency for Sensor Network Nodes Based on Energy Use and Timing Constraints by Youngmin Kim, Heeju Joo, Chan-Gun Lee

“…We analyze the extended model and verify that our algorithm calculates the clock frequency that optimizes energy savings while satisfying the timing constraints.…”
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OPTIMAL DISTRIBUTION NETWORK RECONFIGURATION FOR LOSS MINIMIZATION AND VOLTAGE PROFILE IMPROVEMENT BASED ON ARTIFICIAL INTELLIGENCE by Omar Muhammed Neda

“…The original version of the Dolphin Echolocation Optimization (DEO) algorithm is designed for solving continuous optimization issues only. …”
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GENERATING OF OPTIMAL QUANTIZATION LEVELS OF CONTROL CURRENTS FOR LINEAR STEPPING DRIVES OF PRECISION MOTION SYSTEMS by I. V. Dainiak, V. P. Oger, D. S. Tsitko, D. G. Begun

“…An algorithm for determination of optimal quantization levels of control currents of drive's phases has been developed in the paper; it minimizes an error of positioning that forms correction files for application of a control system in the software. …”
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The optimization of treatment of patients with community-acquired pneumonia with high cardiovascular risk (case from practice). by V. F. Orlovskii, A. V. Zharkova, S. Ya. Udovichenko

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Multi‐objective multi‐period optimal site and size of distributed generation along with network reconfiguration by Ghulam Abbas, Zhi Wu, Aamir Ali

“…To address the pointed‐out challenge of multiperiod optimal DG allocation and reconfiguration while simultaneously decreasing the cost of energy supplied, the cost of energy lost, and the voltage deviation, a novel Multi‐objective Bidirectional co‐evolutionary algorithm (BiCo) is implemented. …”
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Comprehensive Evaluation Method of Teaching Effect Based on Particle Swarm Optimization Neural Network Model by Heng Cao, Qianhui Gao

“…This paper studies the optimization algorithm and optimization system, it not only makes the algorithm involve basic mathematical operations, and the computer support required for the data processing process is not high, but it also improves the evaluation of the degree of optimization. …”
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Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment by Lin Wang, Hui Qu, Shan Liu, Cai-xia Dun

“…Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. …”
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Operational response to contamination in water distribution systems: a multi-objective Bayesian optimization approach by Khalid Alnajim, Ahmed A. Abokifa

“…The optimization framework aims to balance the conflicting objectives of minimizing response time while maximizing water quality metrics after contamination events. …”
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Research on the optimization method of emergency material post transportation model based on bi-level programming by Haixia ZHOU, Yurong MEI, Furu LYU, Zhixin SUN

“…Emergency logistics is a special logistics activity that protects the need of personnel,materials and funds in the event of a major emergency.In the post transportation model of emergency supplies,how to quickly and accurately deliver a large amount of rescue materials to the place of need is a huge challenge to emergency logistics.The logistics cost and the logistics time in the entire logistics process could be minimized by the bi-level planning method while meeting the demand for emergency supplies at the demand point.The bi-level programming model was constructed with the minimum logistics cost of the upper layer and the shortest logistics time of the bottom layer as the goal,and a hybrid tabu search genetic algorithm (HTSGA) was designed to solve the model,which solved the problem of emergency logistics transportation route optimization after the disaster.Finally,the experimental result comparison verified the effectiveness of the model and algorithm.…”
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Designing Multi-Objective Optimization Model of Electricity Market Portfolio for Industrial Consumptions under Uncertainty by Saeed Khalili, Ebrahim Abbasi, Bardia Behnia, Mohammad Amirkhan

“…Due to the small number of industrial subscribers, the whole population was studied. A genetic algorithm has been used to solve this optimization problem. …”
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Efficient Hybrid-Robust Approach for Cancer Biomarker Discovery Using Omics Data by Karima Sid, Soumia Zertal, Mohamed Batouche, Soumeya Zerabi

“…A novel hybrid framework was put forth for consideration, comprising three distinct stages: Clustering, Parallel Filtering, and Hybrid-Parallel Optimization. In each step, a combination of techniques and algorithms is used to improve the results in terms of stability and/or accuracy. …”
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Optimizing low-power, anti-interference routing with IRS through spatiotemporal reinforcement and federated learning by Chengfu Fan, Shoujiu Xiong, Fei Zhou

“…Abstract This paper introduces the SAC-IRS algorithm, a novel approach that combines Intelligent Reflecting Surfaces (IRS) and Reinforcement Learning (RL) to optimize network performance, specifically targeting packet delivery rate and energy efficiency. …”
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