External archive guided radial-grid multi objective differential evolution by Vikas Palakonda, Samira Ghorbanpour, Jae-Mo Kang, Heechul Jung

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Research and application of Gaussian coupled control bistable stochastic resonance system with independent parameter regulation by Tiantian Hou, Shangbin Jiao, Yi Wang, Nianlong Song, Jianghua Li, Wenchuan Cui

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The Application of Support Vector Machine (SVM) in Industrial Carbon Accounting Prediction and Green Electricity Control Strategies by Xu Shasha, Wu Haipeng, Luo Junting, Chen Jian, Jia Huihan

“…This paper, based on the Support Vector Machine (SVM) model, explores its application in industrial carbon accounting, focusing on the interaction between carbon emissions prediction and optimization of control strategies. By analyzing the differences between predicted results and actual carbon emissions data, the paper proposes a series of emission control strategies driven by intelligent algorithms, and discusses them in the context of policy environments and production characteristics. …”
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Distributed Prescribed Finite Time Consensus Scheme for Economic Dispatch of Smart Grids with the Valve Point Effect by Yingjiang Zhou, Shigao Zhu, Qian Chen

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A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…By harnessing dynamic decision-making capabilities of reinforcement learning (RL), we design an optimization architecture centered on the Q-learning mechanism and dual-strategy pools, which is integrated into the honey badger algorithm to form the RL-enhanced honey badger algorithm (RLEHBA). …”
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Research on Functional Modularity and Health Monitoring Design of Home Fitness Equipment by Xinyue Song, Cuiyu Li

“…This study proposes an innovative integrated design framework for multifunctional home fitness equipment, combining modular design, space optimization, and intelligent health monitoring. The design integrates an exercise bike, rowing machine, and spring tensioner into a single unit, reducing equipment footprint by 30% while enabling seamless transitions between exercise modes. …”
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Affine Tensor Product Model Transformation by József Kuti, Péter Galambos

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Enhancing anomaly detection in IoT-driven factories using Logistic Boosting, Random Forest, and SVM: A comparative machine learning approach by Mohammed Aly, Mohamed H. Behiry

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Federated learning for intrusion detection in IoT environments: a privacy-preserving strategy by Ansam Khraisat, Ammar Alazab, Moutaz Alazab, Areej Obeidat, Sarabjot Singh, Tony Jan

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A Comprehensive Overview of the Development and Research of Energy Savings of Electric Wheel Loader by Xiaotao Fei, Zuo Cheng, Shaw Voon Wong, Muhammad Amin Azman, Dawei Wang, Xiuxian Zhang, Qiuchen Shao, Qingqiu Lin

“…Despite their growing technological and environmental significance, a systematic synthesis of advancements in EWL design, energy optimization, and intelligent control remains absent in the literature. …”
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Agile Public Relations in the AI Era: New Paradigms in Digital Media Communication by Samia AOUADJ

“…Consequently, automated systems and advanced algorithms, exemplified by artificial intelligence (AI), present a formidable challenge that goes beyond mere digital existence for these institutions. …”
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Nearest-Better Network-Assisted Fitness Landscape Analysis of Contaminant Source Identification in Water Distribution Network by Yiya Diao, Changhe Li, Sanyou Zeng, Shengxiang Yang

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Beamforming for the Cooperative Non-Orthogonal Multiple Access Transmission with Full-Duplex Relaying with Application to Security Attack by Duckdong Hwang, Sung Sik Nam, Janghoon Yang, Hyoung-Kyu Song

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Multi-Agent Reinforcement Learning in Games: Research and Applications by Haiyang Li, Ping Yang, Weidong Liu, Shaoqiang Yan, Xinyi Zhang, Donglin Zhu

“…Focusing on complex smart city scenarios—including intelligent transportation coordination and UAV swarm scheduling—we identify technical breakthroughs in MARL applications for policy space modeling and distributed decision optimization. …”
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Cost-Effective Autonomous Drone Navigation Using Reinforcement Learning: Simulation and Real-World Validation by Tomasz Czarnecki, Marek Stawowy, Adam Kadłubowski

“…Reinforcement learning machine algorithms designed to solve problems requiring optimization of the solution for the highest possible reward were used. …”
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Research on 3D modeling of underground roadways in coal mines by LIAN Boxiang, MI Langtao, LI Shangjie, GUO Jiyao

“…The Delaunay Triangulation algorithm was adopted to construct an irregular triangular mesh model of the underground roadway, and multi-stage optimization was used to achieve fine 3D reconstruction, which was finally presented via a visualization platform. …”
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Bit flipping-based error correcting output code construction for adversarial robustness of neural networks by Wooram Jang, Woojin Hwang, Kezhong Jin, Hosung Park

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Domain Knowledge-Enhanced Process Mining for Anomaly Detection in Commercial Bank Business Processes by Yanying Li, Zaiwen Ni, Binqing Xiao

“…Our study significantly improves the precision of process anomaly detection in financial contexts by incorporating banking-specific domain knowledge into process mining algorithms. Meanwhile, it extends theoretical boundaries and the practical applicability of process mining in intelligent, semantic-aware financial service management.…”
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SASDL and RBATQ: Sparse Autoencoder With Swarm Based Deep Learning and Reinforcement Based Q-Learning for EEG Classification by Sunil Kumar Prabhakar, Seong-Whan Lee

“…Therefore, taking advantage of these factors, the first method proposed is a Sparse Autoencoder (SAE) with swarm based deep learning method and it is named as (SASDL) using Particle Swarm Optimization (PSO) technique, Cuckoo Search Optimization (CSO) technique and Bat Algorithm (BA) technique; and the second technique proposed is the Reinforcement Learning based on Bidirectional Long-Short Term Memory (BiLSTM), Attention Mechanism, Tree LSTM and Q learning, and it is named as (RBATQ) technique. …”
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Unstructured road semantic segmentation method based on 3D point cloud of open pit mine by Caiwu LU, Jianan XUE, Meng LI, Shengyu YAN, sai ZHANG, Song JIANG, Runfeng HE

“…In order to solve the problems of small size of publicly available unstructured road datasets, uneven sample distribution, and low segmentation accuracy of mainstream point cloud semantic segmentation algorithms for unstructured roads, a semantic segmentation method for unstructured roads in open-pit mine scenarios is proposed by constructing an open-pit mine point cloud dataset through 3D point cloud reconstruction, as well as by optimizing and improving the PointNet++ algorithm. …”
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