Zobrazeno 1 - 10
of 16 121
pro vyhledávání: '"Gradient boosting"'
Publikováno v:
Journal of Accounting in Emerging Economies, 2024, Vol. 14, Issue 5, pp. 1223-1251.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JAEE-07-2023-0205
Autor:
S. Priyadharshini, K. Ramkumar, Subramaniyaswamy Vairavasundaram, K. Narasimhan, S. Venkatesh, Rengarajan Amirtharajan, Ketan Kotecha
Publikováno v:
Alexandria Engineering Journal, Vol 107, Iss , Pp 568-582 (2024)
Parkinson's disease (PD) is the second most prevalent neurological disorder, predominantly affecting older people. With no existing cure, the early detection of PD, where symptoms are not entirely evident but indicative of the disease's onset, is cri
Externí odkaz:
https://doaj.org/article/9c7940e791c54db28c749ce327a944d7
Publikováno v:
Academy Journal of Science and Engineering, Vol 18, Iss 2, Pp 219-238 (2024)
Breast cancer poses a significant global health challenge, being the most prevalent cancer in women and a leading cause of cancer-related mortality. With the increasing number of diagnoses, there is a pressing need for innovative approaches to enhanc
Externí odkaz:
https://doaj.org/article/dc762ba87f91426bba74fefaf4c176fb
Publikováno v:
Вестник Дагестанского государственного технического университета: Технические науки, Vol 51, Iss 3, Pp 72-85 (2024)
Objective. The research aims to detect anomalies in data using machine learning models, in particular random forest and gradient boosting, to analyze network activity and detect cyberattacks. The research topic is relevant as cyber attacks are becomi
Externí odkaz:
https://doaj.org/article/d89dcfddd7194789b9a2270bb2d2d34f
Publikováno v:
International Journal of Information Science and Management, Vol 22, Iss 4, Pp 155-183 (2024)
The aerospace industry and technology are always considered one of the country’s most important and valuable industries. The research area of "Aerospace" is among the priorities of the grand science and technology development strategies, and addres
Externí odkaz:
https://doaj.org/article/5e1dc553b29d4374b99bc3c848cc391f
Autor:
Long Li
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-25 (2024)
Abstract The accurate prediction of uneven rock mass classes is crucial for intelligent operation in tunnel-boring machine (TBM) tunneling. However, the classification of rock masses presents significant challenges due to the variability and complexi
Externí odkaz:
https://doaj.org/article/ba14b42582e24be6bdca94a1cc66e598
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract In this research paper, we explored the predictive capabilities of three different models of Polynomial Regression (PR), Extreme Gradient Boosting (XGB), and LASSO to estimate the density of supercritical carbon dioxide (SC-CO2) and the solu
Externí odkaz:
https://doaj.org/article/9f091c5106b24a3ea559cbdfb7bd2712
Autor:
Sarah A. Alzakari, Amir Abdel Menaem, Nadir Omer, Amr Abozeid, Loay F. Hussein, Islam Abdalla Mohamed Abass, Ayadi Rami, Ahmed Elhadad
Publikováno v:
Alexandria Engineering Journal, Vol 105, Iss , Pp 280-291 (2024)
The advancement of medical technology has brought about a significant transformation in remote healthcare monitoring, which is crucial for providing customized care and ongoing observation. This is especially important when it comes to controlling lo
Externí odkaz:
https://doaj.org/article/1c79ff59193e47c1955f9bc3a8db00df
Autor:
Haewon Byeon
Publikováno v:
Journal of Men's Health, Vol 20, Iss 9, Pp 47-55 (2024)
Hypertension is a significant public health concern, particularly among workers, due to its association with increased risk of cardiovascular and cerebrovascular diseases. This study aimed to identify key factors influencing blood pressure control in
Externí odkaz:
https://doaj.org/article/80d362626b31448f90517a5eefae01f5
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract This study investigates the prediction of ground loss rate during soft-soil shield tunneling using Peck’s back analysis method and XGBoost model. Bayesian optimization is employed to determine optimal hyperparameters, ensuring comprehensiv
Externí odkaz:
https://doaj.org/article/d13708b4dd684afe9916e3a1e076bb17