A Deep Reinforcement Learning Framework for Adaptive Resiliency Enhancement in Smart Power Grids by Boyu Wang, Aliasghar Baziar, Mohammad Reza Askari

“…To overcome these limitations, we propose a deep reinforcement learning framework based on the Deep Deterministic Policy Gradient (DDPG) algorithm, optimized using the Root Mean Square Propagation (RMSprop) method for stable and efficient training. …”
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Lightweight CNN-Based Visual Perception Method for Assessing Local Environment Complexity of Unmanned Surface Vehicle by Tulin Li, Xiufeng Zhang, Yingbo Huang, Chunxi Yang

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Secure healthcare data sharing and attack detection framework using radial basis neural network by Abhishek Kumar, Priya Batta, Pramod Singh Rathore, Sachin Ahuja

“…On the other hand, the proposed intelligent voyage optimization algorithm-based Radial basis neural network (IntVO-RBNN) effectively detects the attacks in the network. …”
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Housing Value Forecasting Based on Machine Learning Methods by Jingyi Mu, Fang Wu, Aihua Zhang

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Advances in the application of machine learning technology in the field of environmental health by ZHENG Yu, LI Cheng, HU Guiping, JIA Guang

“…Among them, advanced machine learning (ML) algorithms can reveal laws that are difficult for humans to detect, showing important potential in biomarker identification, disease prevention, and environmental engineering optimization. …”
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The role of physical metallurgical relationships in enhancing alloy properties prediction and design: A case study on Q&P steel by Yong Li, Hua Li, Chenchong Wang, Pedro Eduardo Jose Rivera‐Diaz‐del‐Castillo

“…To address this, this study proposes a novel framework that combines PM knowledge graphs (PMKGs) with graph neural networks (GNNs) to predict the tensile properties of quenching and partitioning steels, using genetic algorithms for dual‐objective optimization. Compared to traditional artificial intelligence (AI) models, this framework shows significant advantages in predicting ultimate tensile strength (UTS) and total elongation (TEL) with higher accuracy and stability. …”
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Pseudolite Self-Interference Cancellation Without Additional GNSS Signal Distortion by Lichao Gao, Jin He, Yuanxin Wu, Wenxian Yu

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Entropy-driven multi agent deep reinforcement learning for resilient distribution networks: coordinating MESS and microgrids by Changchun Cai, Fenglu Gan, Yong Cui, Bo Li, Shixi Hou

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Conformal Segmentation in Industrial Surface Defect Detection with Statistical Guarantees by Cheng Shen, Yuewei Liu

“…Some machine learning algorithms and artificial intelligence models for defect detection, such as Convolutional Neural Networks (CNNs), present outstanding performance, but they are often data-dependent and cannot provide guarantees for new test samples. …”
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Nash Bargaining-Based Coordinated Frequency-Constrained Dispatch for Distribution Networks and Microgrids by Ziming Zhou, Zihao Wang, Yanan Zhang, Xiaoxue Wang

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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…Finally, the model incorporates these elements (growth points, food locations, obstacles) to analyze and optimize spatial functions.ResultsThe research results indicate that the design method for spatial network analysis using slime mold intelligence based on POI data mapping is highly feasible in the landscape design of small and medium-sized sites. …”
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Virtual Node-Driven Cloud–Edge Collaborative Resource Scheduling for Surveillance with Visual Sensors by Xinyang Gu, Zhansheng Duan, Guangyuan Ye, Zhenjun Chang

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Evaluation of hydraulic fracturing using machine learning by Ali Akbari, Ali Karami, Yousef Kazemzadeh, Ali Ranjbar

“…This integrated approach represents a step forward in applying artificial intelligence for data-driven reservoir engineering and contributes to the advancement of intelligent hydraulic fracturing practices in heterogeneous and data-rich environments.…”
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SDN-Based VANET Routing: A Comprehensive Survey on Architectures, Protocols, Analysis, and Future Challenges by Nehad Hameed Hussein, Johnny Siaw Paw Koh, Chong Tak Yaw, Sieh Kiong Tiong, Foo Benedict, Talal Yusaf, Kumaran Kadirgama, Tan Chung Hong

“…As the automotive and telecommunication industries advance, more vehicles are becoming connected, leading to the realization of intelligent transportation systems (ITS). Vehicular ad-hoc network (VANET) supports various ITS services, including safety, convenience, and infotainment services for drivers and passengers. …”
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Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model by Huan Xu

“…The aim of this study is to propose a novel intelligent approach to predict students’ performance using support vector regression (SVR) optimized by an improved duel algorithm (IDA). …”
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Robust Monocular Visual-Inertial Odometry for Agricultural Vehicles Based on IMU-Augmented 3D Feature Point Correction by Quoc Duy Tran, Quoc Hung Hoang, Gon-Woo Kim

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Machine Learning-Based Network Detection Research for SDNs by Lai Jiayue

“…Reasserting the idea of the critically important role of machine learning for securing SDNs against possible intrusions, these results point not only to the highly beneficial applications of machine learning for protecting SDNs against malicious intrusions but also its indispensable role in preserving network stability and optimizing performance. Moreover, it emphasizes the operational advantage of deploying multiple organic sets of machine learning algorithms, which can achieve even greater precision and efficiency than individual machine learning algorithms in practical uses, bringing it closer to developing a more robust and secure SDN environment.…”
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Game-Theoretic Cooperative Task Allocation for Multiple-Mobile-Robot Systems by Lixiang Liu, Peng Li

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A Literature Analysis-Based Study on Advances in Underwater Multi-Robot Pursuit-Evasion Problems by Zhenkun LEI, Mingzhi CHEN, Daqi ZHU

“…This paper summarizes the application potential and existing issues of current methods in underwater environments and proposes future research directions, including the development of more efficient and adaptive intelligent pursuit-evasion algorithms, so as to address the technical requirements of complex underwater environments and provide theoretical references for designing pursuit-evasion strategies for underwater multi-robot systems.…”
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Graph semantic similarity-based automatic assessment for programming exercises by Chengguan Xiang, Ying Wang, Qiyun Zhou, Zhen Yu

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