Mobile Robot Path Planning Based on Enhanced Dynamic Window Approach and Improved A∗ Algorithm by Hongxia Yang, Xingqiang Teng

“…In the improved A∗ algorithm, in order to improve the algorithm efficiency, so that a single planning path can pass through multiple target points, the search point selection strategy and evaluation function are optimized. …”
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An optimization method of multiscale storage tank target detection introducing an attention mechanism by Wenjia Sun, Chunchun Hu, Nianxue Luo, Qiansheng Zhao

“…Experimental results show that the optimized model significantly improves the detection effect on small targets compared with the original YOLOv5 model. …”
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A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici... by Xinfu Pang, Wen Jia, Haibo Li, Qingzhong Gao, Wei Liu

“…Then, the Monte Carlo method was employed to simulate electric vehicle loads and to facilitate the generation of and reduction in scenario scenes. Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. …”
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Management and prediction of river flood utilizing optimization approach of artificial intelligence evolutionary algorithms by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid

“…These evolutionary algorithms simulate natural processes like selection, mutation, and crossover to optimize flood predictions and management strategies, improving adaptability in dynamic environments. …”
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Quadrotor Robust Fractional-Order Control Based on a Recent Bonobo Optimization Algorithm by Faycal Ziani, Aissa Benhammou, Mohamed Amine Hartani, Hegazy Rezk

“…The five fractional parameters for each engine are also improved using the Bonobo Optimization (BO) algorithm. …”
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Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting by Viktor Godliuk

“…The use of optimization methods, graph algorithms, forecasting, and machine learning to improve the efficiency of digital systems is investigated. …”
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Coupling of green building construction based on particle Swarm optimizing neural network algorithm by Wang Leigang, Li Shaohua, Wang Liang, Zhang Zheng, Zhou Yuchen, Chang Long

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Storage Location Assignment in Emergency Reserve Warehouses: A Multi-Objective Optimization Algorithm by Chen Liang, Tao Cui, Yu Wei, Kun Zhao, Xiongping Yue, Chao Wang

“…Utilizing an advanced non-dominated genetic algorithm (NSGA-II) with an elite strategy, the study conducts simulations and analyses of these models under various scenarios. …”
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Load Frequency Control Based on Gray Wolf Optimizer Algorithm for Modern Power Systems by Dao Huy Tuan, Dao Trong Tran, Van Nguyen Ngoc Thanh, Van Van Huynh

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Optimizing Solid Oxide Fuel Cell Performance Using Advanced Meta-Heuristic Algorithms by Siva Ram Rajeyyagari, Srinivas Nowduri

“…These findings suggest that the AOA method not only offers superior performance but also exhibits the highest convergence among the tested optimization models. This research confirms the potential of advanced optimization techniques in improving the operational parameters of SOFCs, setting the stage for future advancements in fuel cell technologies.…”
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Study on College English Online Teaching Model in Mixed Context Based on Genetic Algorithm and Neural Network Algorithm by Xiaoxia Ma

“…The algorithm avoids subjective errors and improves the accuracy and reliability of the evaluation results, and a comprehensive evaluation model is constructed. …”
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HYBRID FIREFLY AND PARTICLE SWARM OPTIMIZATION ALGORITHM FOR DESIGN OF NON-LINEAR CHANNEL EQUALIZER by Vundavalli Ravindra, Pradyumna Kumar Mohapatra, Ravi Narayan Panda, Saroja Kumar Rout

“…This optimum solution has been modelled using the FFA algorithm, which is driven mainly by light intensity attraction. …”
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Reconstruction of porous media pore structure and simulation effect analysis of multi-index based on SNESIM algorithm by Qing Xie, Jiaqi Gao, Xiaochuang Ye, Jia Li, Yifei Song, Siwen Hu

“…In particular, when dealing with complex pore structures, the accuracy and performance of the SNESIM algorithm need further improvement. Future research will focus on optimizing the algorithm to handle more diverse pore structures and exploring 3D reconstruction methods to more comprehensively describe and analyze the pore characteristics in actual porous media.…”
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Fault diagnosis of ship diesel power distribution system based on WOA-RF algorithm by Weibo LI, Feng GAO, Peng XIAO, Kangzheng HUANG, Daojie RUAN, Junzhuo GAO

“…Therefore, a fault diagnosis method based on whale optimization algorithm-optimized random forest (WOA-RF) is proposed for the marine DG power distribution system.MethodsThe marine DG power distribution system model is built using Matlab/Simulink simulation software. …”
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Three-Dimensional Path Planning Optimization for Length Reduction of Optimal Path Applied to Robotic Systems by Ilias Chouridis, Gabriel Mansour, Apostolos Tsagaris

“…The 2D path is created by a proposed improved artificial fish swarm algorithm (AFSA) that contains several improvements, such as replacing the random behavior of the fish with a proposed one incorporating the model of the 24 possible movement points and utilizing an introduced model to assist the agent’s navigation called obstacles heatmap. …”
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Prediction of compressive strength of fiber-reinforced concrete containing silica (SiO2) based on metaheuristic optimization algorithms and machine learning techniques by Hamed Shokrnia, Ashkan KhodabandehLou, Peyman Hamidi, Fedra Ashrafzadeh

“…So, this study integrates the ANFIS (adaptive neuro-fuzzy inference system) and ELM (extreme learning machine) machine learning models with three optimization algorithms, i.e., WCA (water cycle algorithm), PSO (particle swarm optimization), and GWO (grey wolf optimizer) to precisely estimate the CS of fiber-reinforced concrete (FRC) containing SiO2. …”
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Simultaneous Energy Optimization of Heating Systems by Multi-Zone Predictive Control—Application to a Residential Building by Rina Bitar, Nicolas Youssef, Julien Chamoin, Fadi Hage Chehade, Didier Defer

“…The research methodology uses dynamic thermal simulation, parallel predictive models based on multiple linear regressions, and a multi-objective non-dominated sorting genetic algorithm II (NSGA-II) for the optimization process, which evaluates various generated heating strategies. …”
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Blasting Vibration Control Using an Improved Artificial Neural Network in the Ashele Copper Mine by Shida Xu, Tianxiao Chen, Jiaqi Liu, Chenrui Zhang, Zhiyang Chen

“…In this paper, a genetic algorithm (GA) and an artificial neural network (ANN) algorithm were jointly used to construct a neural network model with a 4-5-1 topology to predict the PPV. …”
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Optimization of dynamic parameters of straddle monorail vehicle to improve pantograph-catenary contact quality by ZHANG Yuejun, YANG Zhen, DU Zixue, WEN Xiaoxia, XU Zhouzhou

“…In order to reduce the abrasion on the sliding block, a sensitivity analysis method was used in this paper to analyze the influence degree of vehicle dynamics parameters on the coupling force of pantograph and catenary based on the dynamic simulation analysis model of "vehicle-pantograph-catenary" system. The average value of the pantograph-catenary contact force was considered as the optimization objective, and dynamics parameters of the vehicle were optimized by non-dominated sorting genetic algorithm (NSGA-II). …”
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A novel approach to intrusion detection system using hybrid flower pollination and cheetah optimization algorithm by Deepshikha Kumari, Prashant Pranav, Abhinav Sinha, Sandip Dutta

“…Abstract The study aims to address critical challenges in network security, particularly the limitations of traditional intrusion detection systems (IDS) in terms of adaptability, detection precision, and high false positive rates in dynamic network environments. A novel hybrid IDS model integrating the Flower Pollination Algorithm (FPA), Cheetah Optimization Algorithm (COA), and Artificial Neural Networks (ANN) is proposed to enhance detection accuracy, reduce false positives, and optimize feature selection, anomaly detection, and rule adaptation. …”
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