A hybrid recommendation system for Chinese character components using a dual-tower neural network and a deterministic algorithm by Shaoqing Yang

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ThermOptCobra: Thermodynamically optimal construction and analysis of metabolic networks for reliable phenotype predictions by Pavan Kumar S, Nirav Pravinbhai Bhatt

“…We present ThermOptCOBRA, a comprehensive solution consisting of four algorithms for optimal model construction and analysis that integrate thermodynamic constraints to address TICs. …”
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Artificial Intelligence and Nature-Inspired Techniques on Optimal Biodiesel Production: A Review—Recent Trends by Christos Kyriklidis, Aikaterini Koutouvou, Konstantinos Moustakas, Vayos Karayannis, Constantinos Tsanaktsidis

“…The optimal fuels are produced in laboratories and tested in common engines too. …”
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A panting behavior-driven assessment framework for summer ventilation quality optimization in layer houses by Zixuan Zhou, Lihua Li, Hao Xue, Yuchen Jia, Yao Yu, Zongkui Xie, Yuhan Gu

“…The YOLOv10-BCE panting behavior detection model was developed by embedding the BiFormer module into the backbone network to enhance multi-dimensional feature extraction, compressing neck structure parameters using the C3Ghost module, and integrating Efficient Intersection over Union (EIOU) loss to improve detection accuracy and convergence speed. …”
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Energy Distribution Optimization in Heterogeneous Networks with Min–Max and Local Constraints as Support of Ambient Intelligence by Alessandro Aloisio, Domenico D. Bloisi, Marco Romano, Cosimo Vinci

“…Additionally, we examine the computational complexity of this model and propose two solution algorithms grounded in fixed-parameter tractability theory for specific network classes.…”
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Advancing Smart Energy: A Review for Algorithms Enhancing Power Grid Reliability and Efficiency Through Advanced Quality of Energy Services by José M. Liceaga-Ortiz-De-La-Peña, Jorge A. Ruiz-Vanoye, Juan M. Xicoténcatl-Pérez, Ocotlán Díaz-Parra, Alejandro Fuentes-Penna, Ricardo A. Barrera-Cámara, Daniel Robles-Camarillo, Marco A. Márquez-Vera, Francisco R. Trejo-Macotela, Luis A. Ortiz-Suárez

“…By concentrating on key aspects—reliability, availability and operational efficiency—the study reviews how various algorithmic approaches, from machine learning models to classical optimisation techniques, can significantly improve power grid management. …”
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Optimization Techniques for Physician Scheduling Problem: A Systematic Review of Recent Advancements and Future Directions by Norizal Abdullah, Masri Ayob, Meng Chun Lam, Nasser R. Sabar, Graham Kendall, Mohamad Khairulamirin Md Razali

“…Future research directions are outlined, emphasizing the need for more scalable algorithms, real-time scheduling capabilities, improved user interfaces, and comprehensive validation studies. …”
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An Edge Container Migration Optimization Method for Multi-service Intelligent Resource Scheduling of Distribution Networks by Shuai LI, Di XU, Xiangyu WEN, Jiaxin ZHANG

“…The simulation results demonstrate that compared with traditional algorithms, the proposed method can validly improve the data processing delay performance for distribution network.…”
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Burning rate research of NEPE propellant containing CL-20 on the base of improved Canny edge detection and PSO-BP by Cai Wenxiang, Yu Xintong, Wang Zhixiang

“…Furthermore, the Particle Swarm Optimization algorithm -Back Propagation neural network model (PSO-BP) is developed for predicting the burning rate, which is compared with the traditional BP algorithm. …”
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Research on Multi-Objective Optimization Design of High-Speed Train Wheel Profile Based on RPSTC-GJO by Mao Li, Hao Ding, Meiqi Wang, Xingda Yang, Bin Kong

“…Secondly, the improved multi-objective optimization algorithm and data-driven model are used to optimize the tread coordinates and obtain an optimized profile. …”
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Quantitative Prediction of Low-Permeability Sandstone Grain Size Based on Conventional Logging Data by Deep Neural Network-Based BP Algorithm by Hongjun Fan, Xiaoqing Zhao, Zongjun Wang, Zheqing Zhang, Ao Chang

“…Machine learning of median grain size from conventional logging data was systematically carried out through conventional logging sensitivity curve optimization, algorithm modeling, network parameter optimization, median grain size prediction, and validation, and the relative error in its quantitative prediction met application requirements. …”
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Reactive power optimization via deep transfer reinforcement learning for efficient adaptation to multiple scenarios by Congbo Bi, Di Liu, Lipeng Zhu, Chao Lu, Shiyang Li, Yingqi Tang

“…Existing reinforcement learning algorithms alleviate the computational complexity in optimization but suffer from the inefficiency of model retraining for different operating scenarios. …”
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Coordinated Scheduling of Distribution Networks and Microgrids Considering Heat Pump Load and Distributed Photovoltaic by Shihui LI, Qi WANG, Xiaobo JIA, Wenchuan WU, Huayang LIANG, Lin ZHU

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Optimization of Cleaning and Hygiene Processes in Healthcare Using Digital Technologies and Ensuring Quality Assurance with Blockchain by Semra Tebrizcik, Süleyman Ersöz, Elvan Duman, Adnan Aktepe, Ahmet Kürşad Türker

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Prediction method of gas emission in working face based on feature selection and BO-GBDT by MA Wenwei

“…In fact, redundant or irrelevant features reduced the model's prediction accuracy. To further improve performance, five hyperparameter optimization algorithms were applied to the GBDT model. …”
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Prediction of Treatment Recommendations Via Ensemble Machine Learning Algorithms for Non-Small Cell Lung Cancer Patients in Personalized Medicine by Hojin Moon, Lauren Tran, Andrew Lee, Taeksoo Kwon, Minho Lee

“…Methods: To accomplish our research goal, we implement ensemble learning algorithms, bagging with regularized Cox regression models and nonparametric tree-based models via Random Survival Forests. …”
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A quasi affine transformation evolution algorithm with evolution matrix selection operation for parameter estimation of proton exchange membrane fuel cells by Mohammad Aljaidi, Pradeep Jangir, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, Samar Hussni Anbarkhan, Laith Abualigah

“…It is challenging to find the best PEMFC parameters because the model is complex and the problem is nonlinear; not all optimization algorithms can solve this problem. …”
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Control Optimization of a Hybrid Magnetic Suspension Blood Pump Controller Based on the Finite Element Method by Teng Jing, Yu Yang, Weimin Ru

“…The results demonstrate that the improved PSO algorithm offers significant advantages over both the BP neural network and traditional manual PID tuning. …”
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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…This algorithm surpasses step control methods optimized through particle swarm optimization and outperforms traditional TD3 reinforcement learning methodologies. …”
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Linear Active Disturbance Rejection Control System for the Travel Speed of an Electric Reel Sprinkling Irrigation Machine by Lingdi Tang, Wei Wang, Chenjun Zhang, Zanya Wang, Zeyu Ge, Shouqi Yuan

“…To enhance the robustness of the control system, it is necessary to investigate new disturbance rejection control algorithms and their effects. Therefore, a kinematic model of the reel sprinkling irrigation machine and a brushless DC (BLDC) motor model were established, and a linear active disturbance rejection control (LADRC) strategy based on improved particle swarm optimization (IPSO) was proposed. …”
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