Improving the area-preserving parameterization of rational Bézier surfaces by rational bilinear transformation by Xiaowei Li, Yingjie Wu, Yaohui Sun, Xin Chen, Yanru Chen, Yi-jun Yang

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Automatic Generation Technology of Safety Measures for Digital Substation Based on Improved Support Vector Machine by Yabing YAN, Xu CHU, Haolong XIAO, Wenwu LIANG, Hui LI, Zhenxing XIA

“…Firstly, construct a secondary circuit model and equipment model based on adjacency matrix, and further integrate the secondary security measure rule library to form a sample dataset; Secondly, support vector machines were used to classify secondary security measures, and bacterial foraging algorithms were introduced to optimize penalty factors and kernel parameters, effectively improving the training effectiveness of the automatic generation model for security measures; Finally, the effectiveness of the proposed method was verified through numerical examples.…”
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A Genetic Algorithm Approach to Adaptive Learning: Enhancing Learner Satisfaction and Performance by Anju Kalwar, Deepika Shekhawat, Sandeep Joshi, Amit Kumar Bairwa

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Integrating evolutionary algorithms and enhanced-YOLOv8 + for comprehensive apple ripeness prediction by Yuchi Li, Zhigao Wang, Aiwei Yang, Xiaoqi Yu

“…For structured text data, support vector regression (SVR) models optimized using the Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA) were utilized to predict apple ripeness, with the WOA-optimized SVR demonstrating exceptional generalization capabilities. …”
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Missile IGC Based on Improved Model Predictive Control and Sliding Mode Observer by Li Ma, Jiayuan Shan, Junhui Liu, Yan Ding

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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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Optimizing Human-Centric Warehouse Operations: A Digital Twin Approach Using Dynamic Algorithms and AI/ML by Erhan Arslan

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GA-VAE: Enhancing Local Feature Representation in VQ-VAE Through Genetic Algorithm-Based Token Optimization by Jinghui Jiang, Dongjoon Kim, Bohyoung Kim, Yeong-Gil Shin

“…This paper introduces GA-VAE, a fine-tuning framework that enhances local feature representation in pre-trained Vector Quantized-VAE (VQ-VAE) models through genetic algorithm-based optimization. …”
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Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity by Xuanli WU, Xu CHEN

“…Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.…”
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Joint energy efficiency and spectral efficiency optimization algorithm for UDN under the restriction of interference threshold and backhaul capacity by Xuanli WU, Xu CHEN

“…Aiming at the scenarios which consider the constraint of backhaul capacity restriction and interference threshold in ultra-dense networks (UDN),an integer linear programming (ILP) and Lagrangian dual decomposition (LDD) based joint optimization algorithm of energy efficiency and spectrum efficiency was proposed.In the proposed algorithms,the user association problem with the constraint of limited backhaul capacity was modelled as an ILP problem and then finished the connection between the user and the base station of microcell by solving this problem with dynamic programming method.Therefor,Lagrangian dual decomposition (LDD) was applied in an iteration algorithm for spectrum resource allocation and power allocation.The simulation results show that compared with traditional schemes,the proposed algorithm can significantly improve the energy efficiency and spectrum efficiency of system and use the microcell’s load capacity more efficiently.…”
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Electrical Equivalent Circuit Parameter Estimation of Commercial Induction Machines Using an Enhanced Grey Wolf Optimization Algorithm by Premkumar Manoharan, Sowmya Ravichandran, Jagarapu S. V. Siva Kumar, Mustafa Abdullah, Tan Ching Sin, Tengku Juhana Tengku Hashim

“…Extensive simulation validation was conducted across various induction motor models, including eight commercial motors, and demonstrated that AWGWO consistently outperforms state-of-the-art algorithms in terms of convergence speed, solution accuracy, and robustness in multimodal optimization landscapes. …”
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Optimized control of parallel heat pump units based on the satin bower bird algorithm in a distributed architecture by Sijia Zhang, Jiangtao Xi, Anjun Zhao, Jun Liu, Yuping Zhang

“…The Distributed Satin Bowerbird Optimization (D-SBO) algorithm is proposed to address the load optimization distribution problem in parallel heat pump units within MDBHE. …”
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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

“…PLO undergoes performance testing against nine established optimization techniques including GSA, DE, PSO, MFO, ACOR, MVO, WOA, SCA, and JAYA through six PEMFC models which include BCS 500 W, Nedstack 600 W PS6, SR-12 W, Horizon H-12, Ballard Mark V, and STD 250 W Stack. …”
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Geological disaster risk assessment based on remote sensing, GIS, and a multi-strategy improved GWO-optimized Elman neural network by Kuayue Chen, Fuhong Bai, Ting Wang, Yingmei Su, Baoyun Wang

“…To improve the accuracy and intelligence of geological disaster risk assessment, this study proposes a novel method based on a Multi-strategy Improved Grey Wolf Optimization algorithm combined with the Elman Neural Network (MIGWO-Elman). …”
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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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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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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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Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting by Farideh Sobhanifard

“…On the other hand, Particle Swarm Optimization is a computational approach, an intelligent optimization, and the most popular algorithm that has been widely used for performing such types of optimization problems, which has faster convergence. …”
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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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Weight optimization of steel lattice transmission towers based on Differential Evolution and machine learning classification technique by Tran-Hieu Nguyen, Anh-Tuan Vu

“…A classification model based on the Adaptive Boosting algorithm is developed in order to eliminate unpromising candidates during the optimization process. …”
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