Zobrazeno 1 - 10
of 2 186
pro vyhledávání: '"support vector regression (svr)"'
Publikováno v:
Engineering Computations, 2024, Vol. 41, Issue 8/9, pp. 2251-2288.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EC-06-2024-0507
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
Abstract Despite extensive efforts to predict optimal nanostructures for enhancing optical devices, a more accurate, efficient, and practical method for nanostructure optimisation is required. In particular, fabrication tolerance is a promising avenu
Externí odkaz:
https://doaj.org/article/2f2c6d8c0b0b4a42933e4c775c5f7e6d
Autor:
Yuzhu Xia
Publikováno v:
Discover Education, Vol 3, Iss 1, Pp 1-14 (2024)
Abstract This study delves into the predictors of English proficiency among middle school students in China, utilizing the rich dataset provided by the China Education Panel Survey (CEPS). By integrating multilevel modeling and Support Vector Regress
Externí odkaz:
https://doaj.org/article/cc59367d80d749c79b22dab6681c2451
Publikováno v:
Case Studies in Construction Materials, Vol 21, Iss , Pp e03628- (2024)
The weak soil stabilization using solid wastes is one of the most common solutions for improving geotechnical characteristics as well as for problematic waste dumping in landfills. The present experimental study aims to examine the effect of high-vol
Externí odkaz:
https://doaj.org/article/c722820af69a42278148348af612da2a
Multi-objective optimization of building energy consumption and thermal comfort based on SVR-NSGA-II
Publikováno v:
Case Studies in Thermal Engineering, Vol 63, Iss , Pp 105368- (2024)
It is necessary to reduce the huge energy consumption of buildings while ensuring indoor thermal comfort. The building envelope design notably affects the energy consumption and indoor thermal comfort. This study proposes a framework of support vecto
Externí odkaz:
https://doaj.org/article/a72c8882eabf4811a41e13f88c481f64
Publikováno v:
Shanghai Jiaotong Daxue xuebao, Vol 58, Iss 6, Pp 806-818 (2024)
Aimed at the intermittency and fluctuation of photovoltaic output power, a short-term interval prediction model of photovoltaic power is proposed. First, the model uses the complete ensemble empirical mode decomposition of adaptive noise (CEEMDAN) to
Externí odkaz:
https://doaj.org/article/6bc936023e594892888cd4b0317dd702
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
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract Estimating penetration rates of Jumbo drills is crucial for optimizing underground mining drilling processes, aiming to reduce costs and time. This study investigates various regression and machine learning methods, including Multilayer Perc
Externí odkaz:
https://doaj.org/article/d8f03364396943f49bcef9576d34f809
Publikováno v:
Journal of Agrometeorology, Vol 26, Iss 3 (2024)
Paddy is a major crop in India which is highly affected by the weather variables resulting in drastic reduction of its yield; adverse all the variables drastically reduce the paddy yield. In this research, machine learning model was developed for pre
Externí odkaz:
https://doaj.org/article/441dc6c043324b94b6cd363046fa0dc3
Autor:
Ha-Eun Yang, Nam-Wook Kim, Hong-Gu Lee, Min-Jee Kim, Wan-Gyu Sang, Changju Yang, Changyeun Mo
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Rice is a staple crop in Asia, with more than 400 million tons consumed annually worldwide. The protein content of rice is a major determinant of its unique structural, physical, and nutritional properties. Chemical analysis, a traditional method for
Externí odkaz:
https://doaj.org/article/b49f6aa0a03f45dcbce0fe21133d6e28