Results 211 to 220 of about 126,268 (270)

Forecasting monthly runoff in a glacierized catchment: A comparison of extreme gradient boosting (XGBoost) and deep learning models [PDF]

PLoS One
Accurate monthly runoff forecasting is vital for water management, flood control, hydropower, and irrigation. In glacierized catchments affected by climate change, runoff is influenced by complex hydrological processes, making precise forecasting even ...
M. Hameed, Adil Masood, Aadil Hamid, Ahmed Elbeltagi, Siti Fatin Mohd Razali, Ali Salem   +5 more
semanticscholar   +2 more sources

A Tutorial and Use Case Example of the eXtreme Gradient Boosting (XGBoost) Artificial Intelligence Algorithm for Drug Development Applications [PDF]

Clin Transl Sci
Approaches to artificial intelligence and machine learning (AI/ML) continue to advance in the field of drug development. A sound understanding of the underlying concepts and guiding principles of AI/ML implementation is a prerequisite to identifying ...
M. Wiens, Alissa Verone‐Boyle, Nick Henscheid, Jagdeep T Podichetty, Jackson Burton   +4 more
semanticscholar   +2 more sources

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Extreme Gradient Boosting for Cyberpropaganda Detection

2021
Propaganda, defamation, abuse, insults, disinformation and fake news are not new phenomena and have been around for several decades. However, with the advent of the Internet and social networks, their magnitude has increased and the damage caused to individuals and corporate entities is becoming increasingly greater, even irreparable. In this paper, we
Jaouhar Fattahi, Mohamed Mejri, Marwa Ziadia   +2 more
openaire   +1 more source

Landslide Susceptibility mapping using random forest and extreme gradient boosting: A case study of Fengjie, Chongqing

Geological Journal, 2023
Landslide susceptibility analysis can provide theoretical support for landslide risk management. However, some susceptibility analyses are not sufficiently interpretable. Moreover, the accuracy of many research methods needs to be improved.
Wen-ge Zhang, Yuwei He, Luqi Wang, Songlin Liu, Xuanyu Meng   +4 more
semanticscholar   +1 more source

Self-trained eXtreme Gradient Boosting Trees

2019 10th International Conference on Information, Intelligence, Systems and Applications (IISA), 2019
Semi-Supervised Learning (SSL) is an ever-growing research area offering a powerful set of methods, either single or multi-view, for exploiting both labeled and unlabeled instances in the most effective manner. Self-training is a representative SSL algorithm which has been efficiently implemented for solving several classification problems in a wide ...
Nikos Fazakis, Georgios Kostopoulos, Stamatis Karlos, Sotiris Kotsiantis, Kyriakos N. Sgarbas   +4 more
openaire   +1 more source

Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach

Journal of Transport Geography, 2021
Active travel has environmental, social, and public health-related benefits. Researchers from diverse domains have extensively studied built-environment associations with active travel.
Jixiang Liu, Bo Wang, Longzhu Xiao
semanticscholar   +1 more source

An Open-Circuit Faults Diagnosis Method for MMC Based on Extreme Gradient Boosting

IEEE transactions on industrial electronics (1982. Print), 2023
The diagnosis of open-circuit faults is required for the reliability of modular multilevel converters (MMC) and the complex operating environment of MMC may cause missing data and external noise in signal detections, where some of the present open ...
Xue Hu, Hefei Jia, Yuedong Zhang, Yan Deng   +3 more
semanticscholar   +1 more source

Extreme Gradient Boosting and Behavioral Biometrics

Proceedings of the AAAI Conference on Artificial Intelligence, 2017
As insider hacks become more prevalent it is becoming more useful to identify valid users from the inside of a system rather than from the usual external entry points where exploits are used to gain entry. One of the main goals of this study was to ascertain how well Gradient Boosting could be used for prediction or, in this case ...
openaire   +1 more source

Extreme gradient boosting and deep neural network based ensemble learning approach to forecast hourly solar irradiance

, 2021
Prediction of solar irradiance is an essential requirement for reliable planning and efficient designing of solar energy systems. Thus, in present work, a new ensemble model, which consists of two advance base models, namely extreme gradient boosting ...
P. Kumari, Durga Toshniwal
semanticscholar   +1 more source

Using extreme gradient boosting (XGBoost) machine learning to predict construction cost overruns

International Journal of Construction Management, 2023
Continuously, cost overruns in construction projects, as a leading cause of project failure, have been attracting more and more attention among construction stakeholders.
G. H. Coffie, S. Cudjoe
semanticscholar   +1 more source