Research on Active–Passive Training Control Strategies for Upper Limb Rehabilitation Robot by Yongming Yang

“…By utilizing neural networks to train sample data during rehabilitation training, the fuzzy rules and membership functions in fuzzy intention recognition algorithm are optimized to improve the accuracy of intention recognition during training. …”
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Research on ionospheric parameters prediction based on deep learning by Yuntian FENG, Xia WU, Xiong XU, Rongqing ZHANG

“…For ionospheric parameter prediction, the short-term and daily mean value prediction of ionospheric parameters was established by long short-term memory (LSTM) predictive neural network modeling.Two methods of point-by-point prediction and sequence prediction were utilized.Furthermore, in order to predict the hourly and daily changes of ionospheric parameters, the proposed scheme was optimized by multidimensional prediction and empirical mode decomposition (EMD) algorithm.Finally, the feasibility of the proposed optimization algorithm in improving the prediction accuracy of ionospheric parameters is verified.…”
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Energy-Efficient Dual-Iteration Power Allocation for Two-Phase Relay System with Massive Antennas by Long Zhao, Wei Xiang, Jie Mei, Hui Zhao, Hang Long, Lin Li

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Deep coal fluidization mining ropeless hoisting system and its cooperative driving control strategy by Shuai LIU, Jiusheng BAO, Jinhao DAI, Yan YIN, Liang ZHAO, Zhongbin WANG, Shirong GE

“…The research results show that the fuzzy PI loop coupling control algorithm can optimize the motor response characteristics and improve the following and synchronization performance among multiple motors. …”
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Risk assessment of tunnel water inrush based on Delphi method and machine learning by Leizhi Dong, Qingsong Wang, Weiguo Zhang, Yongjun Zhang, Xiaoshuang Li, Fei Liu

“…Then, the Radial Basis Function (RBF) network, improved by the Locally Linear Embedding (LLE) algorithm and the Particle Swarm Optimization (PSO), is applied to predict the risk level. …”
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The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China. by Wang Xiang, Zezhi Wang, Xin Pan, Xiaobing Liu, Xuedong Yan, Li Chen

“…Further, the factor traffic control intensity is included in the model. After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. …”
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Robust collaborative mesh networking with large-scale distributed wireless heterogeneous terminals in industrial cyber-physical systems by Tao Wang, Jun Liu, Lianglun Cheng, Hong Xiao

“…Second, the robustness-aware collaborative mesh networking problem is formulated with a multi-objective optimization model, and an improved multi-objective particle swarm optimization algorithm based on self-adaptive evolutionary learning is exploited to search out the Pareto optimal particles with better distribution and diversity. …”
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Neuro-fuzzy controller based adaptive control for enhancing the frequency response of two-area power system by M.S. Elborlsy, Samir A. Hamad, Fayez F.M. El-Sousy, R.M. Mostafa, H.E. Keshta, Mohamed A. Ghalib

“…FPI and PI controllers' parameters are optimally tuned using a recent optimization technique known as the Coati Optimization Algorithm (COA). …”
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Block-Based Adaptive Compressed Sensing by Using Edge Information for Real-Time Reconstruction by V. Pavitra, V. B. S. Srilatha Indira Dutt

“…Adaptive Block-Based Compressed Sensing (ABCS) enables optimization of image and video sensing platforms with limited resources, using novel algorithms for efficient reconstruction and real-time operations. …”
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Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging by Xiaoyu Xue, Haiqing Tian, Kai Zhao, Yang Yu, Ziqing Xiao, Chunxiang Zhuo, Jianying Sun

“…Moreover, two optimization algorithms, namely grid search (GS) and crested porcupine optimizer (CPO), were compared to determine their effectiveness in optimizing the parameters of the SVR model. …”
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Thinning and Weighting of Planar/Conformal Arrays Considering Mutual Coupling Effects by You-Feng Cheng, Wei Shao, Ran Zhang, Xiao Ding, Meng-Xia Yu

“…As an effective optimization algorithm, the differential evolution algorithm (DEA) is adopted in order to achieve low sidelobe. …”
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Enhancing Secure Energy Efficiency of SWIPT IoT Network Considering IRS and Artificial-Noise: A Deep Learning Approach by Kimchheang Chhea, Jung-Ryun Lee

“…We first formulate a joint optimization model of IRS and AN aided secure communication, which is a non-convex optimization problem with linear and non-linear constraints. …”
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Task Offloading with LLM-Enhanced Multi-Agent Reinforcement Learning in UAV-Assisted Edge Computing by Feifan Zhu, Fei Huang, Yantao Yu, Guojin Liu, Tiancong Huang

“…This framework integrates the QTRAN algorithm with a large language model (LLM) for efficient region decomposition and employs graph convolutional networks (GCNs) combined with self-attention mechanisms to adeptly manage inter-subregion relationships. …”
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Hierarchical energy management of distribution network with multi-microgrids based on double Stackelberg game by XIE Yuanhao, LIN Shenghong, ZHU Jianquan

“…By applying the Karush-Kuhn-Tucker (KKT) conditions, the tri-level model is reformulated into a bi-level model, and iterative process combining heuristic algorithm and solver is adopted to solve the model. …”
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Automatic Identification and Segmentation of Overlapping Fog Droplets Using XGBoost and Image Segmentation by Dongde Liao, Xiongfei Chen, Muhua Liu, Yihan Zhou, Peng Fang, Jinlong Lin, Zhaopeng Liu, Xiao Wang

“…In order to accurately measure the droplet size and grasp the droplet distribution pattern, this study proposes a method based on the optimized XGBoost classification model combined with improved concave-point matching to achieve multi-level overlapping-droplet segmentation. …”
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MPDP -medoids: Multiple partition differential privacy preserving -medoids clustering for data publishing in the Internet of Medical Things by Zekun Zhang, Tongtong Wu, Xiaoting Sun, Jiguo Yu

“…Based on the traditional k -medoids clustering, multiple partition differential privacy k -medoids clustering algorithm optimizes the randomness of selecting initial center points and adds Laplace noise to the clustering process to improve data availability while protecting user’s privacy information. …”
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Intelligent Dynamic Trajectory Planning of UAVs: Addressing Unknown Environments and Intermittent Target Loss by Zhengpeng Yang, Suyu Yan, Chao Ming, Xiaoming Wang

“…Additionally, considering future practical applications, the predictor and planner adopt a parallel optimization and correction algorithm structure to ensure planning accuracy and computational efficiency. …”
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Development and Practice of Cloud Collaborative Platform for Downhole Measurement Tools by Che Yang, Yuan Guangjie, Qian Hongyu, Du Weiqiang, Wang Chenlong, Ding Jiping

“…The measurement tools are mainly single machine version， which is difficult to meet the current requirements for improving drilling quality and efficiency. In the paper， based on the remote operation requirements of coreless magnetic steering tool， a platform architecture of five modules， including simulation rehearsal， virtual training， remote operation， smart tool and intelligent decision， was designed in detail， achieving a whole process digitization from predrilling risk assessment and in-drilling acquisition and processing to post-drilling feedback and optimization， and a visual interface was developed. …”
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Advancements in machine learning for estimating parameters of wastewater treatment plants by Kolyeva Natalya, Rastyagaev Alexander, Kortenko Lyudmila, Rozhkov Sergey, Sbitneva Mariia, Kuznetsov Aleksandr

“…As a result of the study, a model of the XGBoost algorithm was developed, which successfully coped with the task of optimization of calculations, providing high accuracy, and this, in turn, opens up new opportunities for improving the efficiency of design of wastewater treatment plants.…”
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Machine learning analysis of pharmaceutical cocrystals solubility parameters in enhancing the drug properties for advanced pharmaceutical manufacturing by Tareq Nafea Alharby, Bader Huwaimel

“…Abstract A new computational framework based on machine learning was developed for prediction of Hansen solubility parameters in preparation of pharmaceutical cocrystals with improved properties. The models of Kernel Ridge Regression (KRR), Multi-Linear Regression (MLR), and Orthogonal Matching Pursuit (OMP) were optimized in prediction of three Hansen solubility parameters. …”
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