Multi-objective optimal scheduling of cascade reservoirs in complex basin systems: Case study of the Jinsha River-Yalong River confluence basin in China by Zhaocai Wang, Zhihua Zhu, Hualong Luan, Tunhua Wu

“…Study focus: Scheduling cascade reservoirs is a high-dimensional, nonlinear multi-objective optimization problem. In complex basins with multiple converging rivers, the ''dimensional catastrophe'' effect increases with more decision variables, requiring improved robustness and optimization of the scheduling algorithm. …”
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EHA-YOLOv5: An Efficient and Highly Accurate Improved YOLOv5 Model for Workshop Bearing Rail Defect Detection Application by Jiyong Hu, Hongfei Yang, Jiatang He, Dongxu Bai, Hongda Chen

“…To validate the superiority of our model, a comparison with popular current models was conducted, achieving optimal values in recall rate, accuracy, and mAP, which were 91.4%, 92.6%, and 88.9%, respectively. …”
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Fault Diagnosis Method for Transformer Winding Based on Differentiated M-Training Classification Optimized by White Shark Optimization Algorithm by Guochao Qian, Kun Yang, Jin Hu, Hongwen Liu, Shun He, Dexu Zou, Weiju Dai, Haozhou Wang, Dongyang Wang

“…The principal contributions are threefold: First, building upon the fundamental principles of the M-training algorithm, we establish a classification model incorporating diversified classifiers. …”
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Multi-objective optimization of grinding process parameters for complicated worm space surface based on the grey wolf optimization algorithm by Jiongkang Ren, Shisong Wang, Keqi Ren

“…To account for actual working conditions, we developed constrained models for grinding ratio and machining rigidity and improved the boundary processing method for MOGWO optimization. …”
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Enhanced Short-Term PV Power Forecasting via a Hybrid Modified CEEMDAN-Jellyfish Search Optimized BiLSTM Model by Yanhui Liu, Jiulong Wang, Lingyun Song, Yicheng Liu, Liqun Shen

“…Each reconstructed component was then forecasted individually using a BiLSTM model, whose parameters were optimized by the JS algorithm. …”
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Energy optimization in intelligent sensor networks: application of particle swarm optimization algorithm in the deployment of electronic information sensing nodes by Wang Liang

“…A Scalable coverage-based particle swarm optimization (SCPSO) algorithm integrates a probabilistic coverage model based on Euclidean distance to detect coverage gaps and guide the optimal positioning of nodes, ensuring that each target within the region of interest is covered by at least one sensor. …”
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Integrated Scheduling Optimization for Multi-Line Production and Transportation of Prefabricated Components Considering Shared Resources by Yiran Dan, Chengshuang Sun, Qianmai Luo

“…This article adopts the genetic algorithm to design the solution algorithm for this model, and the effectiveness of the model and algorithm is verified through an example. …”
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Unlocking The Potential of Hybrid Models for Prognostic Biomarker Discovery in Oral Cancer Survival Analysis: A Retrospective Cohort Study by Leila Nezamabadi Farahani, Anoshirvan Kazemnejad, Mahlagha Afrasiabi, Leili Tapak

“…Then, the particle swarm optimization (PSO) and genetic algorithm (GA) were used in combination with SVR for selecting features related to pseudo-survival outcome. …”
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Automated Generation of Hybrid Metaheuristics Using Learning-to-Rank by Xinru Xue, Ting Shu, Jinsong Xia

“…Metaheuristic algorithms, due to their superior global exploration capabilities and applicability, have emerged as critical tools for addressing complicated optimization tasks. …”
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Prediction of Breakdown Voltage of Long Air Gaps Under Switching Impulse Voltage Based on the ISSA-XGBoost Model by Zisheng Zeng, Bin Song, Shaocheng Wu, Yongwen Li, Deyu Nie, Linong Wang

“…To address this issue, this paper proposes a novel prediction model based on the Improved Sparrow Search Algorithm-optimized XGBoost (ISSA-XGBoost). …”
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Sports video temporal action detection technology based on an improved MSST algorithm by Lai Lixin, Fang Yu

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Application of MRI image segmentation algorithm for brain tumors based on improved YOLO by Tao Yang, Xueqi Lu, Lanlan Yang, Miyang Yang, Jinghui Chen, Hongjia Zhao

“…The remaining 223 images, along with Dataset 2, were ultimately used as the internal test set and external test set, respectively, to evaluate the model’s segmentation effect. A series of optimizations were made to the original YOLOv5 algorithm, introducing the Atrous Spatial Pyramid Pooling (ASPP), Convolutional Block Attention Module (CBAM), Coordinate Attention (CA) for structural improvement, resulting in several optimized versions, namely YOLOv5s-ASPP, YOLOv5s-CBAM, YOLOv5s-CA, YOLOv5s-ASPP-CBAM, and YOLOv5s-ASPP-CA. …”
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Design of Instrumentation and Control Components of Power Distribution Systems by Y. A. Klimenko, Y. E. Lvovich, A. P. Preobrazhensky

“…In recent years, the development of high-voltage power systems has received a boost due to the need for infrastructural support for priority development areas. Universal models and algorithms are required to implement processes in power components and identify their optimal parameters. …”
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Enhanced Automatic Generation Control in Multiarea Power Systems: Crow Search Optimized Cascade FOPI‐TIDDN Controller With Integrated Renewable Solar Thermal Models and HVDC Lines... by Naladi Ram Babu, Pamarthi Sunitha, Ganesh Pardhu B. S. S., Sanjeev Kumar Bhagat, Adireddy Ramesh, Arindita Saha, Wulfran Fendzi Mbasso, Pradeep Jangir, Ahmed Hossam‐Eldin

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A Novel Framework for Improving Soil Organic Carbon Mapping Accuracy by Mining Temporal Features of Time-Series Sentinel-1 Data by Zhibo Cui, Bifeng Hu, Songchao Chen, Nan Wang, Defang Luo, Jie Peng

“…The findings revealed the following: (1) The correlation between time-series S-1 data and SOC exhibited both interannual and monthly variations, with the optimal monitoring period from July to October. The data volume was reduced by 73.27% relative to the initial time-series dataset when the optimal monitoring period was determined. (2) Introducing time-series S-1 data into SOC mapping significantly improved CNN-LSTM model performance (R² = 0.80, RPD = 2.24, RMSE = 1.11 g kg⁻¹). …”
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Optimization Procedures in Affine Model Checking by N. O. Garanina

“…In this paper we suggest improved algorithms for an algebraic data representation, namely, optimization algorithms for affine data structures.…”
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YOLOv8-E: An Improved YOLOv8 Algorithm for Eggplant Disease Detection by Yuxi Huang, Hong Zhao, Jie Wang

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DQN Simulation Model of Green Cooperative Market Behavior of Multi-Load Users for Optimal Evolution of New-Type Power System by ZHANG Shuo, YUAN Chunhui, LI Yingzi, XIAO Yangming, WEI Ming, HE Yunzheng

“…[Methods] First， the green cooperative market behavior and bidding behavior of multiple loads were analyzed and a multiple-load market bidding decision model was constructed. Second， the decision-making process of multiple loads and the entire transaction simulation process of the power market were constructed， and the deep reinforcement learning DQN algorithm was applied to analyze the behavior of multiple loads participating in market transactions and obtain their optimal bidding strategies. …”
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Integration of improved APF and RRT algorithms for enhanced path planning in mobile robotics by Yu Liangwu, Han Jianggui, Ma Boweng, Liu Bao, He Zhiying

“…Firstly, the mathematical model of the traditional APF algorithm was improved to solve the problems of unbalanced force and unreachable targets. …”
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Tracking Control of CSTRs Based on Improved OU Noise and the TD3 Algorithm by Hongyan Shi, Xiaofei Wu, Guogang Wang

“…To enhance exploration capabilities and convergence speed, fractional-order characteristics and a reward feedback mechanism are introduced into the OU noise, dynamically adjusting noise intensity to improve adaptability to complex states and optimize the exploration strategy of the TD3 algorithm. …”
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