Multi-Population Optimization Framework Based on Plant Evolutionary Strategy and Its Application to Engineering Design Problems by Hongwei Cheng, Jun Li, Xiaoming Zhang, Tingjuan Li, Panpan Zhang

“…It outperforms other state-of-the-art optimization algorithms, demonstrating significant improvements in global optimization, solution accuracy, and convergence speed. …”
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Improved faster R-CNN for steel surface defect detection in industrial quality control by Yuefeng Leng, Jiazhi Liu

“…Evaluated on the NEU-DET dataset, the optimized model achieves a mean average precision (mAP) of 80.2%-yielding a 12.6% improvement over the baseline-while increasing detection speed by 40.9%. …”
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Mathematical model of on-demand route formation for public transport based on individual passenger requests in low-density population area by Svetlana S. Titova, Andrey V. Ostroukh

“…Various route optimization algorithms were investigated, and the most suitable method was selected for solving the stated problem. …”
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Algorithm for Solving Distributed Workshop Scheduling Model Based on Order Constraints and Assembly Constraints by Tingting Qu

“…For this model, an improved greedy algorithm was combined to solve it, and particle swarm optimization algorithm was introduced to enhance the local and global search capabilities of the distributed scheduling system, effectively addressing the computational complexity in large-scale production environments. …”
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Hybrid Paddy disease classification using optimized statistical feature based transformation technique with explainable AI by M Amudha, Brindha K

“…To enhance predictive performance by transforming features, an improved Owl Search Optimization (IOSO) algorithm is used. …”
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Study of Fair Strategy for Merchant Self-Operated Takeaway Delivery Based on Delivery Plan Optimization by Jing Chen, Chengbo Guo, Jiahua Kou, Jiali Du, Shufa Sun, Yanling Guo

“…This study presents a mathematical model for merchant-operated takeaway delivery, using an improved ant colony algorithm integrated with K-means to cluster customer locations and determine optimal routes. …”
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Low Carbon Economic Dispatch of Power System Based on Multi-Region Distributed Multi-Gradient Whale Optimization Algorithm by Linfei Yin, Yongzi Ye, Xiaoping Xiong, Jiajia Chai, Hanzhong Cui, Haoyuan Li

“…This study establishes a multi-region distributed optimization model and combines the multi-region distributed optimization model with a multi-gradient optimization algorithm to propose a multi-region distributed multi-gradient whale optimization algorithm (MRDMGWOA). …”
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Classification of Tropical Cyclone Tracks in the Northwest Pacific Based on the SD-K-Means Model by Nan Xu, Baisong Yang, Jia Ren

“…This study proposes an improved SD-K-Means clustering algorithm for classifying TC tracks. …”
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Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints by Manqiong Sun, Yang Xu, Feng Xiao, Hao Ji, Bing Su, Fei Bu

“…The results demonstrate that the initial solutions obtained through the k-medoids clustering algorithm based on spatio-temporal distance improved the overall cost optimization by 1.85% and 4.74% compared to the other two algorithms. …”
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A new CNN deep learning model for computer-intelligent color matching by He Zhibin, Tan Yanmei, Li Sa

“…Besides, based on the optimized algorithm, an intelligent color-matching model was constructed. …”
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Optimization design on process parameters of copper wire bonding for power modules by HU Biao, CHENG Lanxian, LI Zhenling, DAI Xiaoping

“…In order to improve the copper wire bonding performance of the power modules, an optimization design scheme of process parameters for copper wire bonding was proposed by using the six-factor five-level orthogonal test method, and combining the back propagation (BP) neural network and genetic algorithm (GA). …”
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Structure Design and Optimization of Self-locking Under-actuated Gripper by Shuting He, Yi Shen, Xianling Dai, Beibei Qiu, Xianfeng Pan, Mingxin Yuan

“…A structural parameter optimization model is established according to the balance of the clamping force of each gripper knuckle， and a genetic algorithm is introduced to realize the parameter optimization. …”
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Enhancing student success prediction in higher education with swarm optimized enhanced efficientNet attention mechanism. by Meshari Alazmi, Nasir Ayub

“…Moreover, This study develops the proposed EffiXNet, a more refined version of EfficientNet augmented with self-attention mechanisms, dynamic convolutions, improved normalization methods, and Sparrow Search Optimization Algorithm for hyperparameter optimization. …”
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Parameter Adaptive Manta Ray Foraging Optimization for Global Continuous Optimization Problems and Parameter Estimation of Solar Photovoltaic Models by Zhentao Tang, Kaiyu Wang, Yongxuan Yao, Mingxin Zhu, Lan Zhuang, Huiqin Chen, Jing Li, Li Yan, Shangce Gao

“…Furthermore, to enhance population diversity and avoid premature convergence, a randomly selected individual from the top $$ G $$ G high-quality solutions replaces the current best individual in the somersault foraging behavior. Based on these improvements, a parameter adaptive manta ray foraging optimization (PAMRFO) algorithm is developed. …”
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Automatic Generation Algorithm for Power Grid Diagram Based on Power Supply Area by Zhengwei JIANG, Lingyan QUE, Shuming SHA, Fengjian LIU, Xiangyang LIU

“…A mathematical model of station grid uniform diagram layout is built, and an improved force-directed grid layout algorithm is proposed for the supply area. …”
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Wakeup strategy based on multi-objective optimization for fixed relay nodes by Xue-bin MA, Ai-li LI, Xiao-juan ZHANG

“…In order to deal with the “tidal effect” when people move in the city and solve the problem of high energy consumption of fixed relay nodes in opportunistic networks,a wakeup strategy of multi-objective optimization was proposed,which made use of the message forward ability and energy consumption of fixed relay nodes.This strategy used energy efficiency as the indicator to make the nodes awake,and deployed a network revenue-energy consumption model to resolve the contradiction between energy consumption and message forward ability.As the selection problem of awake relay nodes was a NP-hard problem,genetic algorithm was used to select proper fixed relay nodes to keep awake.In this process,selection operator was improved to make the algorithm converge to solution space quickly.Experiments show that the proposed wakeup strategy can guarantee the successful rate of message transmission and improve the average message forwarding capabilities of fixed relay nodes by consuming a unit energy.…”
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Multi-objective multi-workflow task offloading based on evolutionary optimization by Teliekebieke Misha, Lisheng Sun, Zheng-yi Chai

“…Simulation results demonstrate that our algorithm optimally balances delay and energy consumption requirements compared to existing methods, while enhancing the diversity and convergence of non-dominated solutions.…”
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Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy by Yangqing DAN, Lei WANG, Weimin ZHENG, Jiahui WU, Chenxuan WANG, Gaowang YU

“…And then, based on the two-stage robust optimization theory, a strategy model for improving the hosting capacity of the power grid is constructed, and the column and constraint generation (C&CG) algorithm is used to solve the model. …”
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Optimized Application of CGA-SVM in Tight Reservoir Horizontal Well Production Prediction by Chao Wang, Ruogu Wang, Yuhan Lin, Jiafei Zhang, Xiaofei Xie, Zidan Zhao, Yunlin Xu

“…In this paper, chaotic genetic algorithm is used to optimize the traditional support vector machine, and the problems of slow convergence and local convergence are solved by chaotic genetic algorithm, and an improved support vector machine horizontal well production prediction method is established. …”
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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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