Prediction of Electric Vehicle Mileage According to Optimal Energy Consumption Criterion by Oleksii Chkalov, Roman Dropa

“…By representing the road network as a weighted directed graph tailored to the energy consumption model, an algorithm aids in mileage optimization by determining the optimal path for immediate use. …”
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A bi-subpopulation coevolutionary immune algorithm for multi-objective combinatorial optimization in multi-UAV task allocation by Xi Chen, Yu Wan, Jingtao Qi, Zipeng Zhao, Yirun Ruan, Jun Tang

“…Therefore, this paper constructs a Multi-objective Combinatorial Optimization in Multi-UAV Task Allocation Problem (MCOTAP) model, and proposes a Bi-subpopulation Coevolutionary Immune Algorithm (BCIA). …”
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An optimized proportional resonant current controller based genetic algorithm for enhancing shunt active power filter performance by Behnam Amini, Hasan Rastegar, Mohammad Pichan

“…Therefore, by performing accurate and optimal adjustments for APF control, system performance and power quality level can be improved significantly. …”
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Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management by William Alberto Cruz Castañeda, Pedro Bertemes Filho

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RELIABILITY OPTIMIZATION DESIGN ON SHEARER’S RANGING ARM GEAR TRANSMISSION SYSTEM by LI FengJiang, ZHANG Jie, LIAO YingHua, LI QingChen

“…In the process of design shearer ’s ranging arm gear transmission system,by using the method of reliability design theory,derived gear strength and stress assumed to obey normal distribution when tooth surface contact fatigue strength and tooth root bending fatigue strength were taken as constraint conditions,and the volume of gear system as objective function,then genetic algorithm optimization toolbox of MATLAB was used to solve the optimization mathematic model. …”
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Application of adaptive virtual synchronous generator based on improved active power loop in photovoltaic storage systems by Youzhuo Zheng, Yutao Xu, Yekui Yang, Long Hua, Yuqing Yang

“…Then, the adaptive inertia algorithm is incorporated into the active power loop of the VSG control, and an adaptive inertia control method based on the improved active power loop is proposed. …”
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Review on algorithms of dealing with depressions in grid DEM by Yi-Jie Wang, Cheng-Zhi Qin, A-Xing Zhu

“…Existing ways of improving the computation efficiency of depression-processing algorithms are also presented, i.e. serial algorithm optimization and parallel algorithms. …”
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Study on Fault Diagnosis Method of Bearing based on Shuffled Frog Leaping Algorithm to Optimize the BP Neural Network by Wang Yu, Wei Xiuye

“…Through comparison,it is found that the BP neural network model optimized by shuffled frog leaping algorithm can avoid making it fall into local optimum,reduce the training time and improve the training accuracy during the training of the network,and have several advantages,such as relatively higher convergence rate and ability to accurately diagnose.Through a series of training and testing,the results show that this approach can improve the accuracy and reliability of fault diagnosis.…”
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Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm by Xuehui Fan, Ruixue Ye, Yan Gao, Kaiwen Xue, Zeyu Zhang, Jing Xu, Jingpu Zhao, Jun Feng, Yulong Wang

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Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…Second, fuzzy clustering, instead of the softmax classification layer, is employed in ResNet for its characteristic of requiring no subsequent data training. The improved model requires only a small amount of sample training to optimize the parameters of the GAP layer, thereby accommodating state diagnosis in scenarios with limited data availability. …”
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Optimal Configuration of Electricity-Hydrogen Hybrid Energy Storage System Based on Multi-objective Artificial Hummingbird Algorithm by Zijing LU, Zishou LI, Xiangguo GUO, Bo YANG

“…The multi-objective artificial hummingbird algorithm based on Pareto is used to solve the planning scheme and then compared with the multi-objective particle swarm optimization and multi-objective atomic orbital search algorithm. …”
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Optimal operation of multiple integrated energy systems based on a hybrid Taguchi‐compact salp swarm algorithm by Yang Fu, Jie Shan, Zhenkun Li, Bolin Xie

“…Taguchi method can improve the convergence speed and solution accuracy of model. …”
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Double-Layer Optimal Configuration Method of Hybrid Energy Storage System Based on Chaotic Ant Colony Algorithm by Jing Yuan Liu, Xu Yang, Jin Gang Guo, Da Wang, Hai Zhao, Yue Lan

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Optimizing the neural network and iterated function system parameters for fractal approximation using a modified evolutionary algorithm by Sana Abdulla, K. Mahipal Reddy

“…In this study, we propose an evolutionary optimization strategy to enhance the accuracy and adaptability of RFC splines by optimizing their scaling factor and shape parameters using our novel Fractal Differential Evolution (FDE) algorithm. …”
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Quality Evaluation Method for Base Baijiu Based on Support Vector Machine Optimized by Genetic and Bootstrap Aggregating Algorithm by PANG Tingting, ZHANG Guiyu, LIU Kecai, LI Xiaoping, TUO Xianguo, PENG Yingjie, ZENG Xianglin

“…In order to improve the accuracy and generalization capacity of the classification model, a method combining genetic algorithm (GA) and bootstrap aggregating (Bagging) was proposed to optimize the support vector machine (SVM) classifier. …”
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Optimal D-STATCOM placement and sizing using a novel bird swarm operated exploitation of elephant herd algorithm by V. Tejaswini, D. Susitra

“…In the 33-bus system at hour 14, the BSOEEH model achieved optimal results, surpassing established methods by significant margins: 1.06% superior to Grey Wolf Optimizer (GWO), 1.02% superior to Whale Optimization Algorithm (WOA), 1.02% superior to the GWO-WOA hybrid model, 0.13% superior to Elephant Herding Optimization (EHO), and 0.93% superior to Backtracking Search Algorithm (BSA). …”
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An integrated stacked convolutional neural network and the levy flight-based grasshopper optimization algorithm for predicting heart disease by Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Majad Mansoor, Filippo Sanfilippo

“…The SCNN provides robust feature extraction, while LFGOA enhances the model by optimizing hyperparameters, improving classification accuracy, and reducing overfitting. …”
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Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms by Tianyu Li, Xiamin Hu, Tao Li, Jie Liao, Lidan Mei, Huiwen Tian, Jinlong Gu

“…In the initial stage, several classic machine learning models are selected as base models, and the optimal parameters of these models are obtained using the improved metaheuristic-based gray wolf algorithm. …”
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Fast-Charging Optimization Method for Lithium-Ion Battery Packs Based on Deep Deterministic Policy Gradient Algorithm by Zhi Zhang, Taijun Guo, Yefeng Liu, Xinfu Pang, Zedong Zheng

“…The model employs the deep deterministic policy gradient (DDPG) algorithm integrated with reward centralization and entropy regularization mechanisms, aiming to dynamically adjust the charging current to achieve an optimal balance between fast charging and battery health. …”
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Enhancing network lifetime in WSNs through coot algorithm-based energy management model by Namita Shinde, Dr. Vinod H․ Patil

“…This addresses issues such as high energy consumption, communication delays, and security.To ensure energy savings and network reliability, the fitness function evaluates cluster heads and best routes based on constraints.COOT outperforms other Metaheuristics Algorithms like Butterfly Optimization Algorithm, Genetic Algorithm, Tunicate Swarm Gray Wolf Optimization Algorithm, and Bird Swarm Algorithm in simulation with performance measurements and enhancing network functionality and protection.Key methodology points include: • Proposed a multiple constraints clustering and routing technique using COAto solve the most crucial issues that arise in WSNs. • Integrated an advanced fitness function that determines cluster head selection, and the routing path based on residual energy, delay, security, trust, distance, and link quality so that energy load is evenly distributed and credible data flow is maintained across the network and made Innovative and Effective Solution. • Proven Results Demonstrated superior network performance, achieving the lowest delay, highest network lifetime (3571 rounds) and enhanced security (0.8) and trust (0.6) compared to existing algorithms with less energy consumption, making it the most suitable solution for WSN performance improvement.…”
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