Peningkatan Akurasi Metode Weighted Fuzzy Time Series Forecasting Menggunakan Algoritma Evolusi Differensial dan Fuzzy C-Means by Agus Fachrur Rozy, Solimun Solimun, Ni Wayan Surya Wardhani

“…The DE algorithm works by seeking the best solution in a complex parameter space through iterations and performance evaluations, thereby significantly enhancing the performance of the forecasting model. …”
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Intelligent Diagnosis of Rolling Element Bearings Under Various Operating Conditions Using an Enhanced Envelope Technique and Transfer Learning by Ali Davoodabadi, Mehdi Behzad, Hesam Addin Arghand, Somaye Mohammadi, Len Gelman

“…An innovative algorithm is also introduced to identify resonance regions for optimal filter selection in envelope analysis, improving fault-related feature extraction and reducing noise. …”
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Interactive Operation Strategy for Multi-scenario County-Level Multi-microgrid Based on ADMM by Chongbiao ZHANG, Chenwen QIAN, Hongyan YU, Yanling PENG, Jinwei CHEN

“…Firstly, a scheduling model for independent microgrid operation is established to realize the optimal scheduling strategy in the day-ahead pre-scheduling plan. …”
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Enhancing high pressure pulsation test bench performance: a machine learning approach to failure condition tracking by Aslı Aksoy, Ömer Haki

“…Decision tree (DT), gradient boosting tree (GBT), Naïve Bayes (NB), and random forest (RF) algorithms are used to determine the best model. The comparative analysis of ML algorithms revealed that the GBT algorithm exhibits superior predictive capabilities regarding HPPT bench failure predictions. …”
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Multimodal framework for phishing attack detection and mitigation through behavior analysis using EM-BERT and SPCA-BASED EAI-SC-LSTM by Mahmoud Murhej, G. Nallasivan

“…Then, by utilizing Spherical Principal Component Analysis (SPCA), the features are extracted. Further, the optimal features are chosen by using the Cauchy distribution-based Seagull Optimization Algorithm (CSOA). …”
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Short-Term Power Prediction for Wind Farm and Solar Plant Clusters Based on Machine Learning Method by Yang CUI, Zhenghong CHEN, Peihua XU

“…Firstly, the machine learning-based Bisecting K-Means(BKM) clustering algorithm is used to reasonably divide the wind farms and PV stations in the region into clusters; Secondly, based on the correlation between of the historical power data of each power station and the total historical power data in the region, a representative power station is selected for each region; Thirdly, after optimizing and correcting the NWP(numerical weather prediction) model of each representative power station, a short-term power prediction framework model is established using BP neural network based on the cluster division of wind farms and PV power plants. …”
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High-throughput end-to-end aphid honeydew excretion behavior recognition method based on rapid adaptive motion-feature fusion by Zhongqiang Song, Jiahao Shen, Qiaoyi Liu, Wanyue Zhang, Ziqian Ren, Kaiwen Yang, Xinle Li, Jialei Liu, Fengming Yan, Wenqiang Li, Yuqing Xing, Lili Wu

“…Compared with the model excluding the RK50 module, the mAP50 improved by 2.9%, and its performance in detecting small-target honeydew significantly surpassed mainstream algorithms. …”
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Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction. by Kang Xu, Bin Pan, MingXin Zhang, Xuan Zhang, XiaoYu Hou, JingXian Yu, ZhiZhu Lu, Xiao Zeng, QingQing Jia

“…Existing methods, however, have the following limitations: (1) insufficient exploration of interactions across different temporal scales, which restricts effective future flow prediction; (2) reliance on predefined graph structures in graph neural networks, making it challenging to accurately model the spatial relationships in complex road networks; and (3) end-to-end training, which often results in unclear optimization directions for model parameters, thereby limiting improvements in predictive performance. …”
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Adaptive zero velocity correction method for fiber optic inertial navigation system in coal mining roadheader by Qinghua MAO, Qing ZHOU, Jianquan CHAI, Yanzhang CHEN, Wenjuan YANG, Xusheng XUE

“…Secondly, the time-frequency domain features of IMF components are extracted, and the principal component analysis method is used to reduce the dimension to reduce the complexity of the diagnostic model and the difficulty of data analysis. Finally, the accuracy of zero-speed detection is improved by introducing the sandcat swarm optimization algorithm to optimize the kernel function and penalty parameters.Aiming at the problem of high cost and error accumulation with time of high-precision fiber-optic inertial navigation, an adaptive zero-speed correction method is proposed. …”
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Forecast of Photovoltaic Power Based on IWPA-LSSVM Considering Weather Types and Similar Days by Yilun XU, Binqiao ZHANG, Jing HUANG, Xiao XIE, Ruoxin WANG, Danqing SHEN, Lina HE, Kaifan YANG

“…Aiming at the defects of the wolf pack algorithm (WPA), an improved wolf pack algorithm (IWPA) was obtained by improving the walking position and running step of the wolf pack. …”
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A Rice Leaf Area Index Monitoring Method Based on the Fusion of Data from RGB Camera and Multi-Spectral Camera on an Inspection Robot by Yan Li, Xuerui Qi, Yucheng Cai, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaohu Zhang

“…The model based on the LightGBM regression algorithm has the most improvement in accuracy, with a coefficient of determination (R²) of 0.892, a root mean square error (RMSE) of 0.270, and a mean absolute error (MAE) of 0.160. …”
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User Handover Aware Hierarchical Federated Learning for Open RAN-Based Next-Generation Mobile Networks by Amardip Kumar Singh, Kim Khoa Nguyen

“…To address these challenges, we propose MHORANFed, a novel optimization algorithm tailored to minimize learning time and resource usage costs while preserving model performance within a mobility-aware hierarchical FL framework for O-RAN. …”
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Advancing Kidney Transplantation: A Machine Learning Approach to Enhance Donor–Recipient Matching by Nahed Alowidi, Razan Ali, Munera Sadaqah, Fatmah M. A. Naemi

“…Adopting Machine Learning (ML) models for donor–recipient matching can potentially improve kidney allocation processes when compared with traditional points-based systems. (2) Methods: This study developed an ML-based approach for donor–recipient matching. …”
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AI-Assisted Pump Operation for Energy-Efficient Water Distribution Systems by Niuosha Hedaiaty Marzouny, Rebecca Dziedzic

“…The LLM-assisted framework was compared with a genetic algorithm optimization. The results demonstrated that the proposed method outperformed the GA, achieving an energy reduction of 66.98%.…”
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ST-YOLOv8: Small-Target Ship Detection in SAR Images Targeting Specific Marine Environments by Fei Gao, Yang Tian, Yongliang Wu, Yunxia Zhang

“…In summary, the ST-YOLOv8 model, by integrating advanced neural network architectures and optimization techniques, significantly improves detection accuracy and reduces false detection rates. …”
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Experimental Study on Evaluation of Organization Collaboration in Prefabricated Building Construction by Dingjing Bao, Yuan Chen, Shuai Wan, Jinlai Lian, Ying Lei, Kaizhe Chen

“…The knowledge-driven part of this evaluation system used an evaluation model based on the analytic hierarchy process (AHP), while the data-driven part used a prediction model based on the BO-XGBoost algorithm to verify the validity of the AHP-based model. …”
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Research on pedestrian detection technology for mining unmanned vehicles by ZHOU Libing, YU Zhengqian, WEI Jianjian, JIANG Xueli, YE Baisong, ZHAO Yexin, YANG Siliang

“…To tackle issues of missed detections and low accuracy in pedestrian detection, an improved YOLOv3-based pedestrian detection algorithm for mining unmanned vehicles was introduced. …”
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A Novel Framework for Enhancing Decision-Making in Autonomous Cyber Defense Through Graph Embedding by Zhen Wang, Yongjie Wang, Xinli Xiong, Qiankun Ren, Jun Huang

“…Therefore, this paper proposes an enhanced decision-making method combining graph embedding with reinforcement learning algorithms. By constructing a game model for cyber confrontations, this paper models important elements of the network topology for decision-making, which guide the defender to dynamically optimize its strategy based on topology awareness. …”
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A Ship Underwater Radiated Noise Prediction Method Based on Semi-Supervised Ensemble Learning by Xin Huang, Rongwu Xu, Ruibiao Li

“…However, the labeled data available for the training of URN prediction model is limited. Semi-supervised learning (SSL) can improve the model performance by using unlabeled data in the case of a lack of labeled data. …”
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A novel LSTPA methodology for managing energy in electrical/thermal microgrids through CHP, battery resources, thermal storage, and demand-side strategies by Elmira Akhavan Maroofi, Mahmoud Samiei Moghaddam, Azita Azarfar, Reza Davarzani, Mojtaba Vahedi

“…Abstract This paper presents a stochastic optimization model for integrated energy management in electrical and thermal microgrids, addressing uncertainties in renewable energy resources. …”
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