Fault Diagnosis Method of Power Electronic Converter Based on Broad Learning by Ran Han, Rongjie Wang, Guangmiao Zeng

“…In order to realize the unsupervised extraction and identification of fault features in power electronic circuits, we proposed a fault diagnosis method based on sparse autoencoder (SAE) and broad learning system (BLS). …”
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A New Hybrid Machine Learning Method for Stellar Parameter Inference by Sujay Shankar, Michael A. Gully-Santiago, Caroline V. Morley

“…Here we introduce a hybrid ML (HML) method combining automatic differentiation, interpolation, and Bayesian optimization to infer stellar parameters of stellar spectra. …”
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Detection of Attacks in Network Traffic with the Autoencoder-Based Unsupervised Learning Method by Yalçın Özkan

“…It is observed that supervised learning methods lead to difficulties and cost increases in the detection of cyber-attacks and the labeling process. …”
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Retracted: Using Factor Decomposition Machine Learning Method to Music Recommendation by null Complexity

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TDQE：a quality evaluation method for text data in deep learning by LUO Chunxu, XIONG Haixu, YE Yazhen, DING Yan, ZONG Shize, XIONG Yun, ZHU Yangyong

“…To address the issues of high computational costs and incomplete evaluation metrics in existing text data quality assessment methods, a deep learning-oriented text data quality evaluation (TDQE) method was proposed. …”
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Phase diagram construction and prediction method based on machine learning algorithms by Shengkun Xi, Jiahui Li, Longke Bao, Rongpei Shi, Haijun Zhang, Xiaoyu Chong, Zhou Li, Cuiping Wang, Xingjun Liu

“…In the present work, a phase diagram prediction method which integrates machine learning algorithms with CALPHAD descriptors is proposed. …”
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Lightweight Multi-Task Learning Method for System Log Anomaly Detection by Tuan-Anh Pham, Jong-Hoon Lee

“…For log anomaly detection using log sequences, supervised learning methods are preferable due to their high performance. …”
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Deep Reinforcement Learning-Based Deployment Method for Emergency Communication Network by Bo Huang, Yiwei Lu, Hao Ma, Changsheng Yin, Ruopeng Yang, Yongqi Shi, Yu Tao, Yongqi Wen, Yihao Zhong

“…This design effectively mitigates the “curse of dimensionality” inherent in traditional reinforcement learning methods for topology planning. Experimental results demonstrate that the proposed method effectively accomplishes the planning tasks of emergency communication hub elements, significantly improving deployment efficiency while maintaining robustness in complex environments.…”
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Stacking-Based Ensemble Learning Method for the Recognition of the Pedestrian Crossing Intention by Hongjia Zhang, Song Gao, Pengwei Wang

“…Compared with traditional machine learning methods, the proposed method shows greater advantages in recognition accuracy. …”
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DLTM: a deep learning method for tearing mode simulation and prediction by Zhipeng Chang, Baofeng Gao, Ruijie Yin, Xiaofei Zhao

“…In this study, we developed a toolbox called Deep Learning for Tearing Mode, which incorporates two machine learning methods, Tearing-Mode Neural Network and Tearing-Mode Operator Neural Network, to simulate the distributions of perturbation in the linear phase of tearing modes and predict linear growth rates and nonlinear saturated kinetic energy. …”
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Implementation of the Drill Method in Arabic Language Learning at the Elementary Madrasah of the Ummusshabri by Ahmad Futunul Fikri, Khofifah Khofifah, Fauziah Fauziah, Akhbar Susilo

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Orbital Angular Momentum Modes Recognition Method Based on Transfer Learning by Tianyu Du, Jun Ou, Hao Chi, Bo Yang, Shuna Yang, Yanrong Zhai

“…Compared to methods without transfer learning, this approach maintains higher accuracy while significantly reducing the training time and computational resources required. …”
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New Heuristics Method for Malicious URLs Detection Using Machine Learning by Maher Kassem Hasan

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Implementation of the Learning Method of the Prophet Muhammad Saw at Islamic Boarding Schools by Mohammad Wisnu Khumaidi, Agus Maimun, Fadil Fadil

Subjects: “…Islamic Boarding Schools Learning Methods…”
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A Learning Method for Neural Networks Based on a Pseudoinverse Technique by Chinmoy Pal, Ichiro Hagiwara, Naoki Kayaba, Shin Morishita

“…A theoretical formulation of a fast learning method based on a pseudoinverse technique is presented. …”
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Research on deep reinforcement learning based intelligent shop scheduling method by Zihui LUO, Chengling JIANG, Liang LIU, Xiaolong ZHENG, Huadong MA

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Forwarding Collision Assessment with the Localization Information Using the Machine Learning Method by Lei Guo, Yizhen Jia, Xianghui Hu, Feihong Dong

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A Driver’s Calling Behavior Detection Method Based on Deep Learning by XIONG Qunfang, LIN Jun, YUE Wei, LIU Shiwang, LUO Xiao, DING Chi

“…At present, driver’s calling behavior detection methods are prone to object occlusion, image rotation, illumination change and are difficult to extract deep features of the image, which degrade the detection accuracy. …”
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Lightweight deep learning method for end-to-end point cloud registration by Linjun Jiang, Yue Liu, Zhiyuan Dong, Yinghao Li, Yusong Lin

“…In contrast, deep learning-based registration methods have demonstrated improved accuracy and generalization. …”
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Flipped classroom with a gamification case method approach for learning statistics by Novia Kuswidayani, Yerry Soepriyanto, Henry Praherdhiono

“…Research results highlight the success of integrating flipped classrooms with case-based gamification methods, providing an attractive and effective approach to statistics education.   …”
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