Results 11 to 20 of about 32,654 (268)
LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion
Chemometrics and Intelligent Laboratory Systems, 2019 Abstract Protein-protein interactions (PPIs) play an important role in cell life activities such as transcriptional regulation, signal transduction and drug signal transduction. The study of PPIs has become a research hotspot in bioinformatics. However, the identification of PPIs using experimental methods is time-consuming and costly.
Cheng Chen, Bin Yu
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Mathematics, 2023 Long non-coding RNAs (lncRNA) are a class of RNA transcripts with more than 200 nucleotide residues. LncRNAs play versatile roles in cellular processes and are thus becoming a hot topic in the field of biomedicine. The function of lncRNAs was discovered to be closely associated with subcellular localization. Although many methods have been developed to
Lyu, Jianyi +3 more
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An Improved LightGBM Algorithm for Online Fault Detection of Wind Turbine Gearboxes
Energies, 2020 It is widely accepted that conventional boost algorithms are of low efficiency and accuracy in dealing with big data collected from wind turbine operations.
Mingzhu Tang, Steven X Ding, Huawei Wu
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Advanced Payment Security System: XGBoost, LightGBM and SMOTE Integrated [PDF]
2024 IEEE International Conference on Metaverse Computing, Networking, and Applications (MetaCom)This paper is received by https://ieee-metacom ...
Zheng, Qi +5 more
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Application of LightGBM in the Chinese stock market
Proceedings of the 2025 4th International Conference on Big Data, Information and Computer NetworkThis study employs LightGBM, a gradient boosting decision tree model, to predict stock returns and identify key pricing factors in the Chinese A-share market. The empirical analysis yields two main findings. First, LightGBM demonstrates superior predictive performance, achieving a monthly out-of-sample R² of 2.13%, more than doubling the 0.95%
Jie Yang
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Enhancing LightGBM for Industrial Fault Warning: An Innovative Hybrid Algorithm
ProcessesThe reliable operation of industrial equipment is imperative for ensuring both safety and enhanced production efficiency. Machine learning technology, particularly the Light Gradient Boosting Machine (LightGBM), has emerged as a valuable tool for ...
Azadeh Dogani
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Prediction of Ship's Speed Through Ground Using the Previous Voyage's Drift Speed [PDF]
TransNav, 2023 In recent years, 'weather routing' has been attracting increasing attention as a means of reducing costs and environmental impact. In order to achieve high-quality weather routing, it is important to accurately predict the ship's speed through ground ...
Daiki Yamane, Toshiyuki Kano
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Frontiers in Earth Science, 2023 The shear wave velocity (Vs) is significant for quantitative seismic interpretation. Although numerous studies have proved the effectiveness of the machine learning method in estimating the Vs using well-logging parameters, the real-world application is ...
Tianze Zhang +5 more
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Pressure Drop Prediction in Fluidized Dense Phase Pneumatic Conveying using Machine Learning Algorithms [PDF]
Journal of Applied Fluid Mechanics, 2023 Modeling of pressure drop in fluidized dense phase conveying (FDP) of powders is a tough work as the flow comprises of various interactions among solid, gas and pipe wall. It is difficult to incorporate these interactions into a model.
J. s. Shijo, N. Behera
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Using Machine Learning to Analyze the Predictors of Life Satisfaction: Focus on Lifestyle Attitudes and Psychological Factors. [PDF]
Int J Methods Psychiatr ResABSTRACT Objectives Life satisfaction is an essential indicator of quality of life, and enhancing it can contribute to individual well‐being strategies. Because it is a complex concept, a comprehensive approach is needed to address it effectively. Machine learning offers a unique statistical opportunity to address this challenge effectively.
Alptekin FB +7 more
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