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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A Mobile Wireless Sensor Coverage Optimization Method for Bridge Monitoring by Cong Mu, Jiguang Yang, Jiuyuan Huo

“…Aiming at the problem of resource allocation optimization of heterogeneous mobile wireless sensor (HMWS) networks in bridge structural health monitoring, this study proposes an enhanced coverage strategy for heterogeneous sensors based on an improved Hiking Optimization Algorithm (HOA). …”
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Synchronous Remote Calibration for Electricity Meters: Application and Optimization by Zhiyong Zha, Hanfang Ge, Chengcheng Zou, Fei Long, Xingfeng He, Geng Wu, Chenxi Dong, Tianping Deng, Jiaxiang Xu

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Optimizing pyrolysis and Co-Pyrolysis of plastic and biomass using Artificial Intelligence by Manish Sharma Timilsina, Yuvraj Chaudhary, Prikshya Bhattarai, Bibek Uprety, Dilip Khatiwada

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An Improved DeepSORT-Based Model for Multi-Target Tracking of Underwater Fish by Shengnan Liu, Jiapeng Zhang, Haojun Zheng, Cheng Qian, Shijing Liu

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Study on performance optimization for Chinese speech retrieval by ZHENG Tie-ran, HAN Ji-qing, LI Hai-yang

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A survey on autonomous navigation for mobile robots: From traditional techniques to deep learning and large language models by Abderrahim Waga, Said Benhlima, Ali Bekri, Jawad Abdouni, Fatima Zahrae Saber

“…The review extends to modern metaheuristic algorithms, including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). …”
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A Quantum-like Approach to Semantic Text Classification by Anastasia S. Gruzdeva, Rodion N. Iurev, Igor A. Bessmertny, Andrei Y. Khrennikov, Alexander P. Alodjants

“…We also explore methods for reducing the computational cost of algorithms based on the wave model of text representation. …”
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Study on performance optimization for Chinese speech retrieval by ZHENG Tie-ran, HAN Ji-qing, LI Hai-yang

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Automated Class Imbalance Learning via Few-Shot Multi-Objective Bayesian Optimization With Deep Kernel Gaussian Processes by Zhaoyang Wang, Shuo Wang, Damien Ernst, Chenguang Xiao

“…Then, these surrogate models with prior optimization knowledge are combined with the Expected Hypervolume Improvement (EHVI) acquisition function in a Bayesian optimization framework to efficiently discover Pareto-optimal configurations for the target task, which enables AutoCIL-FMOBO to jointly optimize key components, such as resampling methods, classifiers, and their hyperparameters, under a multi-objective setting. …”
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Provide a Solution Based on Teacher and Student Learning Algorithm to Reduce Regression Test Cases by Mahmood Deypir, Amirhossein Mohammadpour

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A Bilevel Programming Approach for Optimizing Multi-Satellite Collaborative Mission Planning by Yi Wang, Desheng Liu

“…Considering the interaction of these decisions, we formulate the problem as a bilevel programming model from a game-theoretic perspective and propose a nested bilevel improved genetic algorithm (NBIGA) for its solution. …”
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A classification model for power corridors based on the improved PointNet++ network by Li Bo, Liu Siyuan, Wang Xiangfeng, Zou Cunyu

“…An improved classification model based on PointNet++ is proposed. …”
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Multi-objective Optimization Design for a Kind of Three-translation Parallel Robot Mechanism by Zhiyuan Ma, Wei Zhu, Hanbing Li, Kanrong Gu, Chuanwei Wang, Jiuwei Shi

“…A kind of 2RRPaR+PPaP three translational space parallel mechanism is designed, and the forward and inverse position solutions equation and Jacobi matrix of the mechanism are derived. The optimization mathematical model is set up with the optimization goal of workspace and global dexterity. …”
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Metaheuristic Algorithm and Laser Projection for Adjusting the Model of the Last Lower Surface to a Footprint by J. Apolinar Muñoz Rodríguez

“…Nowadays, metaheuristic algorithms have been applied to optimize last lower-surface models. …”
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Explainable Model of Fusion Network With Enhanced Optimization Approach for Tuberculosis Diagnosis by C. R. Dhivyaa, K. Nithya, C. Sathiya Kumar, R. Sudhakar

“…The second approach utilizes the EAMSO (Ensemble of AMS Optimization model) for feature selection. It combines the results from AEO (Artificial Ecosystem-based Optimization), MBO (Monarch butterfly optimization), and Seagull-Algorithm to form three optimized feature subsets. …”
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RE-YOLOv5: Enhancing Occluded Road Object Detection via Visual Receptive Field Improvements by Tianyu Li, Xuanrui Xiong, Yuan Zhang, Xiaolin Fan, Yushu Zhang, Haihong Huang, Dan Hu, Mengting He, Zhanjun Liu

“…The proposed method achieves a mean average precision (mAP) of 82.04% on KITTI, representing an improvement of 2.34% over the baseline model. For heavily occluded objects on CityPersons, the Log Average Miss Rate (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>MR</mi><mrow><mo>−</mo><mn>2</mn></mrow></msup></semantics></math></inline-formula>) is reduced to 40.31%, which is a decrease of 9.65% compared to the baseline. …”
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Optimizing the Scheduling of Teaching Activities in a Faculty by Francis Patrick Diallo, Cătălin Tudose

“…This study provides an optimized automated schedule creation technique. The system generates schedules that aim to be conflict-free and efficient, utilizing evolutionary algorithms along with multi-objective optimization. …”
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A Talent Cultivation and Performance Evaluation Model Based on a Fuzzy Control Algorithm by Shanshan Jiang

“…The algorithm combines an adaptive neuro-Fuzzy Inference System with Adaptive Hybrid Particle Swarm Optimization. …”
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A Chaotic Decomposition-Based Approach for Enhanced Multi-Objective Optimization by Javad Alikhani Koupaei, Mohammad Javad Ebadi

“…To address these issues, this paper proposes a chaotic decomposition-based approach that leverages the ergodic properties of chaotic maps to enhance optimization performance. The proposed method consists of three key stages: (1) chaotic sequence initialization, which generates a diverse population to enhance the global search while reducing computational costs; (2) chaos-based correction, which integrates a three-point operator (TPO) and a local improvement operator (LIO) to refine the Pareto front and balance the exploration–exploitation trade-offs; and (3) Tchebycheff decomposition-based updating, ensuring efficient convergence toward optimal solutions. …”
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