Results 21 to 30 of about 33,486 (254)
Using Improved XGBoost Algorithm to Obtain Modified Atmospheric Refractive Index
International Journal of Antennas and Propagation, 2021 Atmospheric refraction is a special meteorological phenomenon mainly caused by gas molecules and aerosol particles in the atmosphere, which can change the propagation direction of electromagnetic waves in the atmospheric environment.
Yanbo Mai +3 more
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Prediction of Gas Emission in the Working Face Based on LASSO-WOA-XGBoost
Atmosphere, 2023 In order to improve the prediction accuracy of gas emission in the mining face, a method combining least absolute value convergence and selection operator (LASSO), whale optimization algorithm (WOA), and extreme gradient boosting (XGBoost) was proposed ...
Weihua Song, Xiaowei Han, Jifei Qi
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XGBoost and Random Forest Algorithms: An in Depth Analysis
Pakistan Journal of Scientific Research, 2023 Machine learning is playing an increasingly important role in many facets of our lives as technology develops, including forecasting weather, figuring out social media trends, and predicting prices on the world market. This significance invoked the demand of some efficient predicting models that can easily handle complex data and provide maximum ...
null Sana Fatima +5 more
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Fault Diagnosis for Wind Turbines Based on ReliefF and eXtreme Gradient Boosting
Applied Sciences, 2020 In order to improve the accuracy of fault diagnosis on wind turbines, this paper presents a method of wind turbine fault diagnosis based on ReliefF algorithm and eXtreme Gradient Boosting (XGBoost) algorithm by using the data in supervisory control and ...
Zidong Wu, Xiaoli Wang, Baochen Jiang
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Diabetes Prediction Based on XGBoost Algorithm
IOP Conference Series: Materials Science and Engineering, 2020 Abstract Exploring important features of diabetes through analytical methods of data mining is able to predict and prevent diabetes. This paper proposes a diabetes prediction algorithm based on XGBoost algorithm with the numerical features being separated while some important features are extracted from the text features of experiment ...
Mingqi Li, Xiaoyang Fu, Dongdong Li
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An Improved XGBoost Indoor Localization Algorithm
DEStech Transactions on Computer Science and Engineering, 2020 This paper proposes an improved XGBoost Wi-Fi indoor positioning algorithm aiming at the accuracy problem caused by the change of environment.The method first uses Extreme Gradient Boosting (XGBoost) algorithm to establish indoor positioning model, which can achieve indoor positioning.
Wei Qiao, Xiaofei Kang, Mengmeng Li
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Remote Sensing Monitoring of Winter Wheat Stripe Rust Based on mRMR-XGBoost Algorithm
Remote Sensing, 2022 For the problem of multi-dimensional feature redundancy in remote sensing detection of wheat stripe rust using reflectance spectrum and solar-induced chlorophyll fluorescence (SIF), a feature selection and disease index (DI) monitoring model combining ...
Xia Jing +4 more
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Optimized Dendritic Cell Algorithm Combined with XGBoost [PDF]
Jisuanji gongcheng, 2019 Dendritic Cell Algorithm(DCA) requires the input of 3 types of signals,which needs to extract features in advance through manual selection or statistics.To extract features accurately and efficiently,a DCA combined with XGBoost is proposed.The XGBoost ...
YANG Chen, LIANG Yiwen, TAN Chengyu, ZHOU Wen
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Comparative Evaluation of Machine and Deep Learning Models for Air Quality Index Prediction in Jaipur, India [PDF]
E3S Web of ConferencesAir pollution is an important environmental and public health challenge, therefore, accurate Air Quality Index (AQI) forecasting is important for timely mitigation.
Banethiwal Parth, Sharma Ruchi
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KNN and XGBoost Algorithms for Lung Cancer Prediction
Journal of Science Technology (JoSTec), 2022 In this paper, the K-Nearest Neighbor and XGBoost algorithms will be implemented in lung cancer prediction. This prediction is important because lung cancer is one of the highest causes of death worldwide. Prediction and diagnosis of this cancer can be done with machine learning algorithms such as K-Nearest Neighbor and XGBoost. Based on the results of
null M. Rhifky Wayahdi, null Fahmi Ruziq
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