Results 1 to 10 of about 16,703 (255)

LightGBM-LncLoc: A LightGBM-Based Computational Predictor for Recognizing Long Non-Coding RNA Subcellular Localization

open access: yesMathematics, 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
Peijie Zheng, Huang Guohua
exaly   +4 more sources

An Improved LightGBM Algorithm for Online Fault Detection of Wind Turbine Gearboxes

open access: yesEnergies, 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
exaly   +3 more sources

LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion

open access: yesChemometrics 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, Qin Ma, Bin Yu
exaly   +3 more sources

Prediction of Ship's Speed Through Ground Using the Previous Voyage's Drift Speed [PDF]

open access: yesTransNav, 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
doaj   +1 more source

Interpretable machine learning model for shear wave estimation in a carbonate reservoir using LightGBM and SHAP: a case study in the Amu Darya right bank

open access: yesFrontiers 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
doaj   +1 more source

Pressure Drop Prediction in Fluidized Dense Phase Pneumatic Conveying using Machine Learning Algorithms [PDF]

open access: yesJournal 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
doaj   +1 more source

Ensemble machine learning approaches for fake news classification

open access: yesРадіоелектронні і комп'ютерні системи, 2023
In today’s interconnected digital landscape, the proliferation of fake news has become a significant challenge, with far-reaching implications for individuals, institutions, and societies.
Halyna Padalko   +3 more
doaj   +1 more source

A simple but effective method for Indonesian automatic text summarisation

open access: yesConnection Science, 2022
Automatic text summarisation (ATS) (therein two main approaches–abstractive summarisation and extractive summarisation are involved) is an automatic procedure for extracting critical information from the text using a specific algorithm or method.
Nankai Lin, Jinxian Li, Shengyi Jiang
doaj   +1 more source

Stock Price Time Series Data Forecasting Using the Light Gradient Boosting Machine (LightGBM) Model

open access: yesJOIV: International Journal on Informatics Visualization, 2023
In the world of stock investment, one of the things that commonly happens is stock price fluctuations or the ups and downs of stock prices. As a result of these fluctuations, many novice investors are afraid to play stocks.
Anggit Dwi Hartanto   +2 more
doaj   +1 more source

Automatic identification of forest species using machine learning methods based on satellite image processing [PDF]

open access: yesИзвестия Саратовского университета. Новая серия: Серия Науки о Земле
Monitoring of the condition and species diversity of tree species plays a significant role in the forest resource management. The emergence of high-quality multispectral satellite images opens up opportunities for using information about vegetation in a ...
Ogneva, Marina V.   +3 more
doaj   +1 more source

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