Zobrazeno 1 - 10
of 3 005
pro vyhledávání: '"random forest (RF)"'
Autor:
LI Yong, ZHAO Xiaohui, LIU Fang, XING Wenge, LI Fengjuan, SHI Jinhai, LIU Jiaxin, YANG Chengmin
Publikováno v:
Zhongguo shuxue zazhi, Vol 37, Iss 10, Pp 1110-1114 (2024)
Objective To systematically analyze and identify key risk factors for postoperative pulmonary hemorrhage using a combination of the random forest (RF) model and traditional logistic regression analysis, so as to provide data support for clinical prac
Externí odkaz:
https://doaj.org/article/c25c45a845da486d9134cd45be6eeacd
Autor:
Hansong Zhu, Feifei Qi, Xiaoying Wang, Yanhua Zhang, Fangjingwei Chen, Zhikun Cai, Yuyan Chen, Kaizhi Chen, Hongbin Chen, Zhonghang Xie, Guangmin Chen, Xiaoyuan Zhang, Xu Han, Shenggen Wu, Si Chen, Yuying Fu, Fei He, Yuwei Weng, Jianming Ou
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-21 (2024)
Abstract Background Influenza outbreaks have occurred frequently these years, especially in the summer of 2022 when the number of influenza cases in southern provinces of China increased abnormally. However, the exact evidence of the driving factors
Externí odkaz:
https://doaj.org/article/5f662e6326bd495cbb8d1ceceb0314d9
Publikováno v:
Geo-spatial Information Science, Pp 1-26 (2024)
The rich feature information contained in the diverse remote sensing data has also exhibited growing potential in the field of image classification. However, the processing of multi-feature data still grapples with the challenges posed by the “curs
Externí odkaz:
https://doaj.org/article/e24307f3997c4f07ae6f4a7475e615ef
Autor:
Hansong Zhu, Si Chen, Weixia Qin, Joldosh Aynur, Yuyan Chen, Xiaoying Wang, Kaizhi Chen, Zhonghang Xie, Lingfang Li, Yu Liu, Guangmin Chen, Jianming Ou, Kuicheng Zheng
Publikováno v:
BMC Infectious Diseases, Vol 24, Iss 1, Pp 1-22 (2024)
Abstract Objective At different times, public health faces various challenges and the degree of intervention measures varies. The research on the impact and prediction of meteorology factors on influenza is increasing gradually, however, there is cur
Externí odkaz:
https://doaj.org/article/001e7eb0e7964a11ab6e2bc6e4d27331
Publikováno v:
Environmental Systems Research, Vol 13, Iss 1, Pp 1-16 (2024)
Abstract A precise and up-to-date Land Use and Land Cover (LULC) valuation serves as the fundamental basis for efficient land management. Google Earth Engine (GEE), with its numerous machine learning algorithms, is now the most advanced open-source g
Externí odkaz:
https://doaj.org/article/1dd3b9b1c72847b1acbb5db5ed169b70
Publikováno v:
Journal of Mechanics of Continua and Mathematical Sciences, Vol 19, Iss 7, Pp 17-27 (2024)
The integration of the Internet of Things (IoT) in medical applications into healthcare applications has enabled the remote monitoring of patients' information, facilitating timely diagnostics as required. The technology of the Internet of Medical Th
Externí odkaz:
https://doaj.org/article/d8e0e90d6b8c4417a045111a6f0c658d
Autor:
Yao Yao, Jianfeng Zhou, Zhenhui Sun, Qingfeng Guan, Zhiqiang Guo, Yin Xu, Jinbao Zhang, Ye Hong, Yuyang Cai, Ruoyu Wang
Publikováno v:
Geo-spatial Information Science, Vol 27, Iss 4, Pp 1000-1016 (2024)
Poverty threatens human development especially for developing countries, so ending poverty has become one of the most important United Nations Sustainable Development Goals (SDGs). This study aims to explore China’s progress in poverty reduction fr
Externí odkaz:
https://doaj.org/article/2fea3f9a168e4d0c9c7c2f48acd7f862
Publikováno v:
Iranian Journal of Electrical and Electronic Engineering, Vol 20, Iss 2, Pp 85-96 (2024)
Cardiovascular arrhythmia is indeed one of the most prevalent cardiac issues globally. In this paper, the primary objective was to develop and evaluate an automated classification system. This system utilizes a comprehensive database of electro- card
Externí odkaz:
https://doaj.org/article/2641ab120d3648baae2cd7d0d02a2a77
Autor:
Guanhong XIAO, Haifeng LU
Publikováno v:
Meikuang Anquan, Vol 55, Iss 6, Pp 184-191 (2024)
Mine sudden water has become one of the main hazards affecting the safety production of mines, and rapid and accurate identification of the type of sudden water source is a key step in the management of mine sudden water disaster, so a PCA-GA-RF-base
Externí odkaz:
https://doaj.org/article/52823b2889dd46528e9ed1766552fc7e
Autor:
Khaled Megahed
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-15 (2024)
Abstract This study explores machine learning (ML) capabilities for predicting the shear strength of reinforced concrete deep beams (RCDBs). For this purpose, eight typical machine-learning models, i.e., symbolic regression (SR), XGBoost (XGB), CatBo
Externí odkaz:
https://doaj.org/article/32078f4efedc4999b980df13c21553fd