Zobrazeno 1 - 10
of 2 833
pro vyhledávání: '"machine-learning techniques"'
Publikováno v:
Discover Artificial Intelligence, Vol 4, Iss 1, Pp 1-15 (2024)
Abstract This study examines factors influencing leisure life satisfaction (LLS) through machine learning techniques based on the data from the 2019 National Leisure Activity Survey in Korea. The results show that using machine learning techniques in
Externí odkaz:
https://doaj.org/article/66cdfad18af14edeaa2f629eec83537c
Publikováno v:
BMC Women's Health, Vol 24, Iss 1, Pp 1-9 (2024)
Abstract Objective The aim of this study is to assess the use of machine learning methodologies in the diagnosis of endometriosis (EM). Methods This study included a total of 106 patients with EM and 203 patients with non-EM conditions (like simple c
Externí odkaz:
https://doaj.org/article/8dae5812f05f4b4e85d7d9b8bec00222
Autor:
Jiefeng Ren, Haijun Wang, Song Lai, Yi Shao, Hebin Che, Zaiyao Xue, Xinlian Qi, Sha Zhang, Jinkun Dai, Sai Wang, Kunlian Li, Wei Gan, Quanjin Si
Publikováno v:
BMC Cardiovascular Disorders, Vol 24, Iss 1, Pp 1-9 (2024)
Abstract Objective Accurate prediction of survival prognosis is helpful to guide clinical decision-making. The aim of this study was to develop a model using machine learning techniques to predict the occurrence of composite thromboembolic events (CT
Externí odkaz:
https://doaj.org/article/a9cbfd5b640b48c586dca0423a0989bb
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 103048- (2024)
Precise streamflow forecasting in river systems is crucial for water resources management and flood risk assessment. The Tagus Headwaters River Basin (THRB) in Spain is a key hydrological hub, providing regulated flow for agricultural, urban, and ene
Externí odkaz:
https://doaj.org/article/2887e077568a4a2295c71857b68f5333
Autor:
Pedro Luis Saraiva Barbosa, Gabriela Nayara Duarte Oliveira Damazio, Windson Viana de Carvalho, Rafael Augusto Ferreira do Carmo, Evandro Nogueira de Oliveira
Publikováno v:
Avaliação: Revista da Avaliação da Educação Superior, Vol 29 (2024)
Abstract Accreditation and continuous assessments are crucial for ensuring quality and standards in higher education. In Brazil, the federal government also conducts an annual student assessment called Enade. This paper presents a scoping review that
Externí odkaz:
https://doaj.org/article/ac7d6ecaba274e2b912702e99c127221
Autor:
Ahmet Durap
Publikováno v:
Results in Engineering, Vol 24, Iss , Pp 103573- (2024)
Accurate prediction of significant wave height (SWH) is critical for coastal safety, marine operations, and disaster management. Traditional numerical models for wave prediction are computationally intensive and often lack accuracy, prompting a shift
Externí odkaz:
https://doaj.org/article/0c968d7b35364734ae1233e71fb4d283
Publikováno v:
China Finance Review International, 2023, Vol. 14, Issue 2, pp. 310-331.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/CFRI-12-2022-0250
Publikováno v:
Misan Journal of Engineering Sciences, Vol 3, Iss 1, Pp 100-120 (2024)
The subject of study known as radio propagation prediction refers to predicting the behaviour and characteristics of radio waves as they propagate through the atmosphere. It is a basic element of all wireless communication systems, including satellit
Externí odkaz:
https://doaj.org/article/5f72e0d2068d499fbc86c198740cd845
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 19, Iss 2, Pp 1493-1516 (2024)
Sentiment analysis is a cornerstone of natural language processing. However, it presents formidable challenges due to the intricacies of lexical diversity, complex linguistic structures, and the subtleties of context dependence. This study introduces
Externí odkaz:
https://doaj.org/article/e49fd313d6fb42f08268106becce9e35
Publikováno v:
Al-Iraqia Journal for Scientific Engineering Research, Vol 3, Iss 3 (2024)
Recent advancements in machine learning have played a crucial role in the healthcare industry, particularly in predicting heart disease with assorted datasets. Despite the registration results indicating promising accuracy and resilience in heart dis
Externí odkaz:
https://doaj.org/article/828da4c682d641d59e21136605140164