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Three-Dimensional Trajectory Tracking Control for Stratospheric Airship Based on Deep Reinforcement Learning
Published 2025-01-01“…The Boltzmann random distribution of reward value and probability of wind direction angle were taken as the action selection criteria of the Q-learning algorithm, the cerebellar model articulation controller (CMAC) neural network was constructed for the discrete action value, and the optimal action sequence was fast obtained. …”
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Research and predictive analysis of pyrolysis characteristics of multi-source organic solid wastes
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Optimization of electric vehicle charging facility layout considering the enhancement of renewable energy consumption capacity and improvement of PSO algorithm
Published 2025-04-01“…To deal with the optimization model, the particle swarm optimization is adopted and improved in three aspects. These three improvements include randomly updating inertia weights, introducing acceleration factors to replace learning factors, and introducing fast non-dominated sorting for better or worse selection, and improving the optimization ability of the algorithm by solving the crowding distance. …”
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Use of Machine Learning to Predict the Incidence of Type 2 Diabetes Among Relatively Healthy Adults: A 10-Year Longitudinal Study in Taiwan
Published 2024-12-01“…Ultimately, 6687 adults were included in the final analysis, where we implemented three different ML algorithms, including logistic regression (LR), random forest (RF) and extreme gradient boosting (XGBoost) in order to predict diabetes. …”
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Enhancing Security in DNP3 Communication for Smart Grids: A Segmented Neural Network Approach
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Measuring Online Battery AC Resistance Using a DC-DC Converter With Time and Frequency Hybrid Method
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Optimisation of Aluminium Alloy Variable Diameter Tubes Hydroforming Process Based on Machine Learning
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Chinese Massage (Tuina) Attenuates Knee Osteoarthritis by Modulating Autophagy-Related Cytokines: A Multidisciplinary Methodological Investigation
Published 2025-08-01“…Zhen Wang,1,* Chi Zhao,1,2,* Mengmeng Li,1,2,* Lili Zhang,1,* Jieyao Diao,1 Yiming Wu,2 Tao Yang,2 Mingwei Shi,2 Yang Lei,2 Yu Wang,3 Miaoxiu Li,4 Yanqin Bian,5 Yunfeng Zhou,1 Hui Xu1,2 1College of Acupuncture and Massage, Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 2Acupuncture and Massage Department, The Third Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, People’s Republic of China; 3College of Computer Science, Xidian University, Xian, People’s Republic of China; 4College of Acupuncture and Massage, Shanghai University of Chinese Medicine, Shanghai, People’s Republic of China; 5Orthopaedic Research Laboratory, University of California, Davis, CA, USA*These authors contributed equally to this workCorrespondence: Hui Xu, Email 15036065036@163.comBackground: Tuina therapy has demonstrated its potential in modulating autophagy-related factors in knee osteoarthritis (KOA); however, its core therapeutic targets and specific mechanisms require systematic elucidation through interdisciplinary research.Objective: This study investigated the mechanism by which Tuina alleviates KOA progression using multidimensional approaches, including Mendelian randomization (MR), in vivo experiments, and machine learning.Methods: Genetic data from genome-wide association studies of 60 cytokines and KOA were analyzed using MR analysis to identify autophagy-related factors significantly associated with KOA. …”
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Applications of Multi-Robotic Arms to Assist Agricultural Production: A Review
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Missing values imputation using Fuzzy K-Top Matching Value
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Robotic Hand–Eye Calibration Method Using Arbitrary Targets Based on Refined Two-Step Registration
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Multi-objective Windy Postman Problem in a Fuzzy Transportation Network
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The coverage method of unmanned aerial vehicle mounted base station sensor network based on relative distance
Published 2020-05-01“…The simulation results show that the coverage of the proposed algorithm is 22.4% higher than that of random deployment, and it is 9.9%, 4.7% and 2.1% higher than similar virtual force-oriented node, circular binary segmentation and hybrid local virtual force algorithms.…”
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Enhancing Software Defect Prediction Using Ensemble Techniques and Diverse Machine Learning Paradigms
Published 2025-07-01“…The prediction of software defects is a crucial element in maintaining the stability and reliability of software systems. This research addresses this need by combining advanced techniques (ensemble techniques) with seventeen machine learning algorithms for predicting software defects, categorised into three types: semi-supervised, self-supervised, and supervised. …”
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