Results 11 to 20 of about 13,208 (247)
Stock Price Time Series Data Forecasting Using the Light Gradient Boosting Machine (LightGBM) Model
JOIV: 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
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Automatic identification of forest species using machine learning methods based on satellite image processing [PDF]
Известия Саратовского университета. Новая серия: Серия Науки о ЗемлеMonitoring 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
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UWB Wireless Positioning Method Based on LightGBM
Wireless Personal Communications, 2023 Abstract In the ultra-wideband indoor positioning sceneraio, the non-line of sight (NLOS) propagation may be caused by obstacles, which may lead to the deviation of ranging value and affect the positioning precision. Therefore, we propose a NLOS identification and error regression positioning algorithm based on light gradient boosting machine ...
Xuerong Cui +5 more
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LIGHT GRADIENT BOOSTING MACHINE FOR OPTIMIZING CROP MAINTENANCE AND YIELD PREDICTION IN AGRICULTURE [PDF]
ICTACT Journal on Soft ComputingIn agriculture, optimizing crop yield and maintenance practices is essential for ensuring food security and sustainable farming. Traditional approaches often lack the efficiency needed to process large agricultural datasets and accurately predict yield ...
Sunil Kumar +3 more
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Atmosphere, 2023 The atmospheric environment is of great importance to human health. However, its influencing factors are complex and variable. An efficient technique is required to more precisely estimate PM2.5 concentration values.
Xuehu Liu +3 more
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Dianxin kexue随着经济的发展和一线城市生活压力的增大，越来越多的人迁移城市以及返回家乡发展，为了高效服务用户和提升用户产品使用体验，提出基于LightGBM、CatBoost等算法来预测返乡发展人群，并进行了异构模型融合。通过模型对比，所提融合模型有更好的效果，可以为服务和产品提供依据，减少流失优化感知，提高市场保有率。
杜昭1, 谢国城2, 陈静旋2, 张伟斌1
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Human action recognition method based on multi-view semi-supervised ensemble learning
网络与信息安全学报, 2021 Mass labeled data are hard to get in mobile devices. Inadequate training leads to bad performance of classifiers in human action recognition. To tackle this problem, a multi-view semi-supervised ensemble learning method was proposed.
CHEN Shengnan, FAN Xinmin
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Frontiers in PharmacologyBackgroundIn the intensive care unit (ICU), septic patients frequently require endotracheal intubation followed by invasive mechanical ventilation. Nonetheless, the optimal sedation-analgesia regimen for these critically ill patients remains undetermined.
Qinxue Hu +4 more
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A comparative classification framework using PCA and modified PCA with ensemble and kernel-based learning models for mangrove feature analysis [PDF]
BIO Web of ConferencesHyperspectral image (HSI) classification remains challenging due to high spectral dimensionality, redundancy among bands, and limited labeled samples, particularly in high–spatial-resolution agricultural and coastal environments.
Saha Chowdhury Arpita +2 more
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A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
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