This book contains the selected proceedings of the 2025 International Conference on Machine Learning, Cloud Computing and Intelligent Mining, held in Mohe, China, July 21-25, 2025. The conference explores advances and practical applications in Machine Learning and Control Systems, Robot, and delves into innovative approaches in two specialized tracks: Machine Learning and Control Systems, and Cloud Computing and Intelligent Mining.

It explores optimizing reinforcement learning for robotic control in industrial automation, using cloud computing for intelligent networked robot systems, and applying machine learning to telerobotics control.MLCCIM2025 Conference provides a forum for bringing together the various groups working in the area of machine learning algorithms for robotic control, cloud computing - enabled intelligent systems, and data mining techniques in mining operations to exchange views and report research findings.

Provide valuable resources for researchers and practitioners in machine learning, control systems, and robotics Introduces the recent trends and new horizons in machine learning research Gathers best research papers presented at MLCCIM2025

Autorentext

Huaming Wu (Senior Member, IEEE) received the BE and MS degrees from the Harbin Institute of Technology, China, in 2009 and 2011, respectively, both in electrical engineering, and the PhD degree with the highest honor in computer science from Freie Universität Berlin, Germany, in 2015. He is currently a professor with the Center for Applied Mathematics, Tianjin University, China. His research interests include mobile cloud computing, edge computing, Internet of Things, deep learning, complex networks, and DNA storage.

Guohui Tian (Member, IEEE) was born in Hejian, China, in 1969. He received the B.S. degree from Shandong University, Jinan, China, in 1990, the M.S. degree from the Shandong University of Technology, Zibo, China, in 1993, and the Ph.D. degree from the School of Automation, Northeastern University, Shenyang, China, in 1997. From 1999 to 2001, he was a Post-Doctoral Researcher with the School of Mechanical Engineering, Shandong University. From 2003 to 2005, he was a Visiting Professor with the Graduate School of Engineering, The University of Tokyo, Tokyo, Japan. He was a Lecturer from 1997 to 1998 and an Associate Professor from 1998 to 2002 with Shandong University, where he is currently a Professor with the School of Control Science and Engineering. His current research interests include service robot, intelligent space, cloud robotics, and brain-inspired intelligent robotics. He is a member of the IEEE Robotics and Automation Society. He is also the Vice-Director of the Intelligence Robot Specialized Committee of Chinese Association for Artificial Intelligence and the Intelligent Manufacturing System Specialized Committee of Chinese Association for Automation.

Hongqi Yu received the B.S., M.S., and Ph.D. degrees from the National University of Defense Technology (NUDT), Changsha, China, in 2000, 2003, and 2007, respectively.,He is an Associate Professor at NUDT. He was an Academic Visitor at Center for Biophotonics, University of Strathclyde, Glasgow, U.K., from June 2014 to July 2015. His research interests focus around signal processing, SPAD based FLIM system and embedded system.

Inhalt

A Threat Evaluation and Jamming Allocation System against STAP Radar Based on Double Q-learning and Chaos Genetic Algorithm.- Affective Disorder Detection in College Students with Weak-Privacy Rhythmical Behavioral Data from Smartphones.- Experimental Verification of Machine Vision-Based Pose Recognition Method for Bell-and-spigot Joint Shield Segments.- Multi-Source Spatio-Temporal Feature Fusion Network For Short-Term Wind Power Forecasting.- Attention-Aware Graph Contrastive Learning for Movie Recommendation Services.- Semantic Structure-Aware Sequential Recommendation.- Lightweight Category-level 6D Pose Estimation Based on Knowledge Distillation.- GGO-GA: A Hybrid Group Geese OptimizationGenetic Algorithm for Efficient Feature Selection in Software Defect Prediction.- Intelligent Diabetes Detection System Using Machine Learning Techniques.- DTR-DDQN: A Reinforcement Learning Framework for Delay-Tolerant Joint Path Selection and Task Offloading.- Transmission Line Insulator Defect Detection with Improved YOLOv11.- MTDW-RAG: A Tree-Structured Medical Q&A Approach Combining Deep Progression and Wide Exploration.- BGDSO: A new synthetic oversampling method based on bilateral gradient distribution for imbalanced data.- Multimodal Sleep Stage Classification Method based on Multi-channel Convolution and Neural Ordinary Differential Equations.- An Overview and Benchmark Evaluation of RNA Representation Learning Methods.- Prediction and Analysis of Olympic Medal Distribution Using a Hyperparameter-Optimized Random Forest Algorithm.- Cross Domain Adaptation for Online Map Generation from Optical Remote Sensing Image via Diffusion Model.- DEAM: Knowledge-Aware Retrieval with Dynamic Evidence Grounding.- Structure-Aware Transformer for Code Snippet Summarization.- A Remote Sensing Image Visual Grounding Method Based on Multi-Subspace Feature Fusion.- AEB: A Method for Augmentation and Preprocessing of Maritime Small Target Datasets Based on Dual Channels of Image Enhancement and Background Suppression.- Enhanced DQN based Parameter Optimization for VSG Control under Pulsed Power Loads.- AI on edge Deploying for Real-Time Analytics.- Research on Dynamic Prediction Model for Building Energy Consumption Based on EWC-SI.- Method for Detecting Material High-temperature Phase Transition Dynamic Region based on Dynamic Event Coding.- Surrogate-assisted Hybrid Multiobjective Evolutionary Neural Architecture Search.- Crack Detection Based on Multi-Algorithm Fusion of Deep Learning and Image Processing.- Research on Decision Support System for Multi-step Complex Attacks.- Binding Pruning Method via Channel Slimming for Efficient YOLOv5 Object Detection.- STSACM: A Method for Segmenting and Classifying Subjects in Chinese Electronic Medical Records.- Deep Reinforcement Learning for Adaptive Radar Jamming: A Markov Decision Process Approach to Cognitive Electronic Warfare.- Research on Multi-Agent Formation Control Method Based on Curriculum Learning and Improved PD Algorithm.- An Optimization Method for Collaborative Task Planning Strategy Based on the Improved Practical Byzantine Fault-tolerant Algorithm.- Intelligent Bandwidth Management and Reliability Control in SDN-enabled Cellular Core Networks.- Small Target Detection Algorithm for Air-to-ground Based on C2Dgnet.- Self-attention and Unet-based Lossy Image Compression.- Novel Brain Tumor Detection Model Based on YOLO with Multi-Module Fusion.- RefineChain: A Dual-phase Refinement Framework for Complex Question Decomposition in Large Language Models.- Deep Learning-Based Image Registration for Train Chassis.- A Prediction Model for Air Pollution based on GATTL Spatiotemporal Model.- Industrial Surface Defect Detection Method Based on Improved YOLOv11.- An Improved RDE-YOLOV10 Algorithm for Campus Conflict Behavior Recognition.- Research on the Influence of Activation Functions on the Performance of Convolutional Neural Networks and the Effect of Channel Pruning.- Reinforcement Learning-Based Motion Control of Jellyfish Millirobots.- A Detection Method for Alzheimer's Disease based on Multimodal Deep Learning.- A Stomach Recognition Method Based on TransUnet and Dual Attention Mechanism.- Short-Term Load Forecasting of Integrated Energy System Based on Spatio-Temporal Graph Neural Network.- Long Text Matching Model with Multi-Granularity Feature-Hierarchical Filtering.- LLM-based Challenging Data Augmentation for Aspect-based Sentiment Analysis.- Deep Learning-Based Feature Selection for Movie Recommendation Services.- Data Re-Uploading in Quantum Kernels: A Hybrid Approach for Tabular Data Classificat…