Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 by Qing Jiang, Ruipeng Gao, Yan Zhao, Wenzhen Yu, Zhuofan Dang, Shiyi Deng

“…The experimental results demonstrate that, in comparison with the currently prevalent mainstream target detection algorithms, the improved model can attain optimal recall rates R, mAP@0.5, and mAP@0.5:0.95. …”
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Collaborative Optimization of Container Liner Slot Allocation and Empty Container Repositioning Within Port Clusters by Wenmin Wang, Cuijie Diao, Wenqing He, Zhihong Jin, Zaili Yang

“…Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and algorithm. The results show that the new collaborative optimization method, incorporating the cooperative possession strategy and (T, s) inventory policy, can increase liner company revenues by expanding market share, reducing costs, and improving the utilization of slot resources, ultimately achieving a win–win outcome for both liner companies and their partners. …”
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Multi-layer Embedded Optimization of Microgrid Capacity Considering Price and Incentive/Compensation Coupling Mechanism by Xianhui ZHU, Xu HU, Nan SHI, Yao ZHANG, Jingwen ZHONG

“…Finally, the optimization models of both the source and load are coupled through the multi-layer embedded mechanism, and a solution model is constructed, which combines the multi-objective particle swarm optimization (MOPSO) algorithm and the particle swarm optimization–imperial competition algorithm (PSO-ICA). …”
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Distributed Risk-Averse Optimization Scheduling of Hybrid Energy System with Complementary Renewable Energy Generation by Yanbo Jia, Bingqing Xia, Zhaohui Shi, Wei Chen, Lei Zhang

“…A risk-averse operation optimization model is proposed using conditional value at risk to quantify the uncertainty of renewable energy generation. …”
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A Novel RMS-Driven Deep Reinforcement Learning for Optimized Portfolio Management in Stock Trading by Asma Sattar, Amna Sarwar, Saira Gillani, Maryam Bukhari, Seungmin Rho, Muhammad Faseeh

“…This study proposed an improved stock market trading framework termed the RMS-Driven Deep Reinforcement Learning (DRL) model for optimal portfolio management. …”
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A GIS-based integrative approach for land use optimization in a semi-arid watershed by S.M. Tajbakhsh, H. Memarian, A. Kheyrkhah

“…In line with the management of natural resources, land use optimization can be highly useful. The aim of the present study is to propose an appropriate integrative model for optimized allocation of lands for surface runoff and sediment load minimization and net income maximization in Bayg watershed, Iran. …”
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Shield tunneling efficiency and stability enhancement based on interpretable machine learning and multi-objective optimization by Wenli Liu, Yang Chen, Tianxiang Liu, Wen Liu, Jue Li, Yangyang Chen

“…On this basis, a multi-objective intelligent optimization model is established to solve the optimized operating parameters of shield machine by non-dominated sorting genetic algorithm II and technique for order preference by similarity to ideal solution to reduce GS and improve drilling efficiency. …”
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Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…The proposed model trained with all weeks’ data demonstrated superior performance, showing significant improvements in F1-scores and recall, particularly for the minority class of at-risk students. …”
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UAV-based multitier feature selection improves nitrogen content estimation in arid-region cotton by Fengxiu Li, Fengxiu Li, Chongqi Zhao, Chongqi Zhao, Yingjie Ma, Yingjie Ma, Ning Lv, Yanzhao Guo, Yanzhao Guo

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Optimizing Scheduled Virtual Machine Requests Placement in Cloud Environments: A Tabu Search Approach by Mohamed Koubàa, Abdullah S. Karar, Faouzi Bahloul

“…Our algorithm demonstrates significant improvements over existing placement methods, achieving up to a 15% increase in resource efficiency compared to baseline approaches. …”
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A Novel Method of Self-Healing Concrete to Improve Durability and Extend the Service Life of Civil Infrastructure by Yan Xue, Weiliang Gao, Yanming Zhao

“…Moreover, a concrete durability prediction model based on particle swarm optimization-least squares support vector machine (PSO-LSSVM) and improved NSGA-II (nondominated sorting genetic algorithm II) algorithm was proposed to quickly and accurately determine the optimization scheme of self-healing concrete mix proportion. …”
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Performance optimization of active RIS-assisted near-shore dual-function radar communicaiton system by XU Miao, YUE Dianwu, SUN Yu, WU Xiangkai, YUAN Meng

“…An alternating optimization algorithm based on fractional programming theory and the Lagrangian operator method was proposed. …”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…A multi-objective optimization model is also established, further illustrating the algorithm’s performance and its effectiveness in balancing the number of sensors and coverage rate. …”
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Tooth Profile Modification Method of RV Reducer Cycloid Gear Aiming at Optimizing Carrying Capacity by Zongwen An, Panlong Jia, Qiang Wang, Zhili Li, Mingyuan Lei

“…Cycloid gear tooth profile modification is very important to the performance of RV reducer，in order to select the shape modification method and parameter size reasonably and improve the stress state of the cycloid tooth surface，an equidistant & radical-moving modification method based on particle swarm optimization algorithm to optimize bearing capacity is proposed. …”
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Multi-strategy enhanced artificial rabbits optimization for prediction of grades in tourism service communication courses by Xiaodan Qu, Zhuyin Jia

“…Results indicate that MEARO outperforms these algorithms. Furthermore, MEARO is used to optimize two critical parameters of the Kernel Extreme Learning Machine (KELM), significantly improving its classification performance. …”
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Hate Speech Detection and Online Public Opinion Regulation Using Support Vector Machine Algorithm: Application and Impact on Social Media by Siyuan Li, Zhi Li

“…Detecting hate speech in social media is challenging due to its rarity, high-dimensional complexity, and implicit expression via sarcasm or spelling variations, rendering linear models ineffective. In this study, the SVM (Support Vector Machine) algorithm is used to map text features from low-dimensional to high-dimensional space using kernel function techniques to meet complex nonlinear classification challenges. …”
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DBO-DELM Method for Predicting Rolling Forces in Cold Rolling by LI Xiaoyang, PIAO Chunhui, WANG Xuelei, ZHANG Mingzhi

“…Aiming at the problems of many assumptions, large computational errors and poor generalisation performance of the traditional rolling force prediction model, a cold rolling force prediction model (DBO-DELM) using the dung beetle optimizer algorithm (DBO) to optimise the deep extreme learning machine (DELM) is proposed. …”
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Many-objective optimization scheduling of cascade reservoirs in small watersheds based on an evolutionary multitasking framework by Zheng Wang, Rui Dai, Wanliang Wang, Jing Jie, Qianlin Ye

“…This study develops a many-objective optimization scheduling model for cascade reservoirs in the Lushui River Basin and proposes a constrained many-objective evolutionary multitasking optimization algorithm (EMCMOA) to solve it. …”
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Optimizing chemotherapeutic targets in non-small cell lung cancer with transfer learning for precision medicine. by Varun Malik, Ruchi Mittal, Deepali Gupta, Sapna Juneja, Khalid Mohiuddin, Swati Kumari

“…For dimensionality reduction, the modified Rime optimization (MRO) algorithm is used to select the best features among multiples. …”
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Optimal Decision-making Method of Wind-proof and Disaster-resistant Reinforcement Measures for Distribution Network by Xin GAO, Fei TANG, Tongyan ZHANG, Yu LI

“…The reinforcement strategy was further optimized through the particle swarm optimization algorithm, considering the total reinforcement budget, the load importance and the component fragility. …”
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