Design of intelligent optimization of sports strategy and training decision support system based on deep reinforcement learning by Hua Xu, Bing Lin, Long Liu

“…The data is preprocessed by a sliding window average filter algorithm to eliminate noise and outliers. The system adopts the DQN (Deep Q-Network) architecture and applies dual DQN technology to improve model stability. …”
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Sparse Adaptive Optimization Based on Low Rank Decomposition for Image Defect Detection by Daihong Jiang, Zhixiang Chen, Sanyou Zhang, Yunfei Li, Lu Zhao

“…To solve the resulting optimization problem efficiently, we develop a tailored algorithm based on operator splitting techniques, significantly improving computational efficiency without sacrificing accuracy. …”
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Optimizing additive manufacturing workflows using model-based systems engineering by Mohamed Amine Daoud, Khadija Bekkay Haouari, Meriem Hayani Mechkouri, Amine Ennawaoui, Hicham El hadraoui, Ilias Naser, Mustapha Ouardouz, Kamal Reklaoui

“…Future iterations of ASAM will incorporate advanced algorithms for real-time parameter optimization and predictive analytics. …”
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Research on Multi-objective Shielding Intelligent Optimization Method Based on Non-dominated Sorting Genetic Algorithm NSGA-Ⅲ by WANG Mengqi, ZHENG Zheng, MEI Qiliang, PENG Chao, GAO Jing, ZHOU Yan

“…This meticulous process resulted in the selection of a series of improved shielding solutions. In addition, a realistic 3D Monte-Carlo computational model was built to rigorously evaluate the shielding effectiveness of these optimized solutions. …”

Optimization of the Screw Conveyor Device Based on a GA-BP Neural Network by Qiang Guo, Yunpeng Zhuang, Houzhuo Xu, Wei Li, Haitao Li, Zhidong Wu

“…In this paper, we analyze the force and velocity components acting on the straw, give the design principles for the screw’s conveying parameters under the premise of ensuring maximum conveying capacity and minimum power consumption, and determine the optimal design variables, objective functions, and constraints according to the specific optimization problem; we establish a specific mathematical model, and introduce algorithm optimization for nonlinear problems with many variables and large amounts of calculations. …”
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Improved Prediction of Hourly PM_2.5 Concentrations with a Long Short-Term Memory Optimized by Stacking Ensemble Learning and Ant Colony Optimization by Zuhan Liu, Xianping Hong

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Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms by Juchao Chen, Zicheng Lei, Zongcai Duan, Zhili Wen

“…Abstract This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in hepatocellular carcinoma, establish a prediction model for spontaneous rupture bleeding via a machine learning algorithm, and validate and evaluate the predictive efficacy of the model. …”
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A levy chaotic horizontal vertical crossover based artificial hummingbird algorithm for precise PEMFC parameter estimation by Pradeep Jangir, Absalom E. Ezugwu, Kashif Saleem, Arpita, Sunilkumar P. Agrawal, Sundaram B. Pandya, Anil Parmar, G. Gulothungan, Laith Abualigah

“…The combination of this method with PEMFC parameters results in a significantly improved performance compared to traditional methods, such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Grey Wolf Optimizer (GWO), and Sparrow Search Algorithm (SSA), which we use as baselines to validate PEMFC parameters. …”
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Model-Free Attitude Control of Spacecraft Based on PID-Guide TD3 Algorithm by ZhiBin Zhang, XinHong Li, JiPing An, WanXin Man, GuoHui Zhang

“…Aiming at this problem, the PID-Guide TD3 algorithm is proposed, which can speed up the training speed and improve the convergence precision of the TD3 algorithm. …”
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Big Data and AI Algorithms for Sustainable Development Goals: A Topic Modeling Analysis by Prema Nedungadi, Simi Surendran, Kai-Yu Tang, Raghu Raman

“…AI applications notably improve healthcare by advancing disease tracking, tailored treatments, and precision medicine, fostering universal healthcare and reducing noncommunicable disease mortality. …”
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Soft detection model of corrosion leakage risk based on KNN and random forest algorithms by Yang YANG, Chengzhi LI, Xuan DU, Xiao YU, Shaohua DONG

“…Future research efforts should focus on enhancing data acquisition and analysis techniques, optimizing the model structure, and improving the model adaptability and accuracy across various application scenarios.…”
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Robust dispatch for electrical–thermal combined smart building considering impacts of uncertainties on thermal side by Weijie He, Fanrong Wei, Xiangning Lin, Samir M. Dawoud

“…The close connection between electrical energy and thermal energy is an important attribute of current smart buildings. Most previous works aim to emphasize the important role of the power side, thus neglecting the accuracy of the thermal side model. …”
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Metaheuristic Optimization of Wind Turbine Airfoils with Maximum-Thickness and Angle-of-Attack Constraints by Jinane Radi, Jesús Enrique Sierra-García, Matilde Santos, Carlos Armenta-Déu, Abdelouahed Djebli

“…The drag and lift coefficients are estimated, and a metaheuristic optimization technique, genetic algorithm, is applied to maximize the glide ratio while reducing the difference from the desired design parameters. …”
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Optimal ecological restoration strategy development based on value-cost trade-offs by Yunxuan Liu, Cui Zhang, Miaomiao Xie, Jingyi Xie

“…In addition, we searched for Pareto-optimal solutions using the nondominated sorting genetic algorithm II (NSGA-II) to balance the trade-offs between different objectives. …”
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Rolling Bearing Fault Diagnosis Based on Optimized VMD and SSAE by Baoxian Chang, Xing Zhao, Dawei Guo, Siyu Zhao, Jiyou Fei

“…Firstly, the DBO algorithm is enhanced to improve its optimization precision and global optimization capability. …”
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Multi-objective design optimization of a transonic axial fan stage using sparse active subspaces by Richard Amankwa Adjei, Chengwei Fan

“…Active subspace was used to compute the active variables via singular value decomposition and a hybrid polynomial correlated function expansion was used to construct a surrogate model on the active subspace. Coupled with freeform method and multi-objective genetic algorithm, an automated optimization loop was run at a single operating condition. …”
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An improved multiple adaptive neuro fuzzy inference system based on genetic algorithm for energy management system of island microgrid by Yanming Cheng, Jinqi Zhang, Mahmoud Al Shurafa, Dejun Liu, Yulian Zhao, Chao Ding, Jing Niu

“…EMS is a control system integrated within MGs for managing the operations of these DGs effectively to fulfill a power balance between power production and load demand in the most optimal way, especially in island MGs. In this paper, an EMS based on Multiple Adaptive Neuro-Fuzzy Inference System optimized by Genetic Algorithm (MANFIS-GA) is proposed for PV/Wind/Diesel Generator/Battery (PWDB) island MG system, to optimize the output power of diesel generator, manage charging-discharging operation of MG Battery Storage keeping its State of Charge (SOC) in acceptable limits, and improve the MG system reliability and stability by mitigating the effects of sudden changes in the electrical loading and Renewable energy sources (RES) Power. …”
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Research on LSTM-PPO Obstacle Avoidance Algorithm and Training Environment for Unmanned Surface Vehicles by Wangbin Luo, Xiang Wang, Fang Han, Zhiguo Zhou, Junyu Cai, Lin Zeng, Hong Chen, Jiawei Chen, Xuehua Zhou

“…In response to the above problems, this paper proposes a long and short memory network-proximal strategy optimization (LSTM-PPO) intelligent obstacle avoidance algorithm for non-particle models in non-ideal environments, and designs a corresponding deep reinforcement learning training environment. …”
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Deep Reinforcement Learning-Based Two-Phase Hybrid Optimization for Scheduling Agile Earth Observation Satellites by Guanghui Zhou, Zhicheng Jin, Dongning Liu

“…The experimental results demonstrate that the TPHO framework with MRC rules achieves superior performance, yielding a total reward improvement exceeding 16% compared with the A-ALNS algorithm in the most complex scenario involving 1200 tasks, yet requiring less than 3% of the computational duration of A-ALNS.…”
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Optimizing Hyperparameters in Meta-Learning for Enhanced Image Classification by Amala Mary Vincent, P. Jidesh, A. A. Bini

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