Non-intrusive load identification method based on VMD and PSO-SVM by YANG Rui, ZOU Xiaosong, XIONG Wei, YUAN Xufeng, ZHENG Huajun, LIU Bin

“…In view of the advantage of variational mode decomposition (VMD) in signal processing, a load identification algorithm based on variational mode decomposition and fast independent component analysis (VMD-FastICA) and variational mode decamposition-entropy-particle swanm optimization fo optimizing support vector machines (VMD-Entropy-PSOSVM) is proposed. …”
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Reinforcement Learning and Multi-Access Edge Computing for 6G-Based Underwater Wireless Networks by Juan Carlos Cepeda-Pacheco, Mari Carmen Domingo

“…In the aquatic domain, the Internet of Underwater Things (IoUT) represents a global network of intelligent underwater devices designed to capture, interpret, and share data. …”
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Rapid detection method for pork freshness using fusion spectroscopy and improved BAS-LSSVM by WANG Yao, REN Xiaozhen

“…Analyze the performance of the proposed method through experiments.ResultsThe experimental method could achieve accurate, rapid, and non-destructive testing of pork freshness (TVB-N), with high detection accuracy and efficiency, the detection correlation coefficient was 0.978 1, the mean square error was 0.302 1, and the average detection time was 0.031 seconds.ConclusionA fast non-destructive testing method for meat freshness (TVB-N) can be achieved by combining spectral detection and intelligent algorithms.…”
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An Improved Adaptive Car-Following Model Based on the Unscented Kalman Filter for Vehicle Platoons’ Speed Control by Caixia Huang, Wu Tang, Jiande Wang, Zhiyong Zhang

“…The proposed approach offers a practical solution for coordinated platoon speed control in intelligent transportation systems, with promising application prospects for real-world implementation.…”
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A new enhanced TDEEC protocol for 3D HWSN by Ouiam Amenchar, Mostafa Baghouri, Saad Chakkor, Aziz Dkiouak

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Strategic Implementation of Super-Agents in Heterogeneous Multi-Agent Training for Advanced Military Simulation Adaptability by Huseyin Oktay Altun, Huseyin Furkan Ceran, Korkut Kutay Metin, Tolga Erol, Emre Fisne

“…This study focuses on the application of reinforcement learning in tactical military simulation environments involving heterogeneous multi-agent systems. Optimizing Heterogeneous Multi-Agent Training (HMAT) through scenario-specific adjustments to the Proximal Policy Optimization (PPO) algorithm, we tackle the complexity of tactical simulations. …”
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An Empirically Validated Framework for Automated and Personalized Residential Energy-Management Integrating Large Language Models and the Internet of Energy by Vinícius Pereira Gonçalves, Andre Luiz Marques Serrano, Gabriel Arquelau Pimenta Rodrigues, Matheus Noschang de Oliveira, Rodolfo Ipolito Meneguette, Guilherme Dantas Bispo, Maria Gabriela Mendonça Peixoto, Geraldo Pereira Rocha Filho

“…This study explores a novel framework—MELISSA (Modern Energy LLM-IoE Smart Solution for Automation)—that integrates Internet of Things (IoT) sensor networks with Large Language Models (LLMs) to optimize household energy consumption through intelligent automation and personalized interactions. …”
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Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

“…This work employs single hidden layer extreme learning machine (ELM) algorithm and hybrid particle swarm optimization-based support vector regression (PS-SVR) for determining energy storage efficiency of high-entropy ceramics. …”
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Building Fire Location Predictions Based on FDS and Hybrid Modelling by Yanxi Cao, Hongyan Ma, Shun Wang, Yingda Zhang

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Investigation and application of data balancing and combined discriminant model in rock burst severity prediction by Shaohong Yan, Runze Liu, Yanbo Zhang, Xulong Yao, Yueqi Yang, Qi Wang, Bin Guo, Shuai Wang

“…Ultimately, a BO-MLP-RF composite prediction model was constructed based on Bayesian Optimization (BO), Multilayer Perceptron (MLP), and Random Forest (RF) algorithms, with the Bayesian Optimization method ensuring that the model fits the training data well and generalizes to the test data. …”
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Study on Subway Station Street Block-Level Land Use Pattern and Plot Ratio Control Based on Machine Learning by Mingyi Kuang, Fei Fu, Fangzhou Tian, Liwei Lin, Can Du, Yuesong Zhang

“…As urbanization accelerates, megacities are facing challenges such as inefficient land use and traffic congestion, particularly in the context of rail transit-oriented development, where land use optimization remains a significant research gap. Current urban planning still relies heavily on the experience and intuition of government planning departments, without achieving quantitative, intelligent, and scientific decision making. …”
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Research on rolling bearing compound fault diagnosis based on AMOMCKD and convolutional neural network by Runfang Hao, Yunpeng Bai, Kun Yang, Yongqiang Cheng, Shengjun Chang

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Frequency stabilization of a sophisticated multi-area interconnected hybrid power system considering non-inertia sources by Diaa M. Gawad, Gaber Magdy, M.A. Ebrahim, Eduard Petlenkov

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Quality management of the chemical-technological process for continuous synthesis of pharmaceutical substances of medicinal compounds in flow microreactors by V. F. Kornyushko, O. M. Nikolaeva, A. V. Panov, R. R. Biglov, A. S. Kuznetsov

“…To manage the quality of the process of continuous APS synthesis in the flow microreactor, we developed theoretic multiple system models that were designed to build the digital information environment for the process of experimental research. We developed algorithms for mathematical modeling and optimization of the control process based on multiresponse regression models and an online optimization algorithm that allows the process to be managed step by step, taking into account the limitations. …”
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Decision-making method for residual support force of hydraulic supports during pressurized moving under fragmented roof conditions in ultra-thin coal seams by ZHANG Chuanwei, ZHANG Gangqiang, LU Zhengxiong, LI Linyue, HE Zhengwei, GONG Lingxiao, HUANG Junfeng

“…Furthermore, the Dung Beetle Optimization (DBO) algorithm was enhanced with ICMIC chaotic mapping, Lévy flight, and a greedy strategy, yielding the IDBO algorithm with improved optimization accuracy and faster convergence. …”
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Tomato leaf disease detection method based on improved YOLOv8n by Ming Chen, Chunping Wang, Chengwei Liu, Ying Yu, Yuan Yuan, Jiaxuan Ma, Kaisheng Zhang

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Remote Sensing Image Detection Method Combining Dynamic Convolution and Attention Mechanism by Yunfei Zhang, Ming Chen, Cong Chen

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Multilayer entropy-weighted TOPSIS method and its decision-making in ecological operation during the subsidence period of the Three Gorges Reservoir by Ai Xueshan, Yu Yangxin, Liang Zhiming, Shi Xuanyu, Cao Rui, Zhang Xiaoke

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Enhancing Power Quality in Grid-Integrated Hybrid Renewable Energy System using ANFIS-FBSO by Singh Manpreet, Singh Lakhwinder

“…To achieve these goals, a multi-resolution proportional-integral-derivative (MRPID) controller, alongside an ANFIS-FBSO-based controller in series and a shunt active power filter (SAPF), is used to address PQ issues in current and voltage, thereby enhancing UPQC performance. The FBSO algorithm optimises the learning function of the ANFIS for optimal outcomes. …”
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Method and application of stability prediction model for rock slope by Yun Qi, Chenhao Bai, Xuping Li, Hongfei Duan, Wei Wang, Qingjie Qi

“…To accurately and efficiently predict the stability state of slopes, we propose a combined model that integrates the Newton–Raphson optimization algorithm (NRBO) with an optimized extreme gradient boosting tree (XGBoost). …”
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