Zobrazeno 1 - 10
of 11 421
pro vyhledávání: '"Polynomial regression"'
Autor:
Haiyan Zhang, Shuwei Sun
Publikováno v:
BMC Psychology, Vol 12, Iss 1, Pp 1-23 (2024)
Abstract Background In past decades, the Chinese government has enacted a series of ecological policies to encourage organizations, the pivotal institutional agents implementing national policies, and employees, the crucial micro-actors engaging in e
Externí odkaz:
https://doaj.org/article/71ab78fa9b294cd885de301296f2e276
Autor:
Wulfran Fendzi Mbasso, Reagan Jean Jacques Molu, Ambe Harrison, Mukesh Pushkarna, Fritz Nguemo Kemdoum, Emmanuel Fendzi Donfack, Pradeep Jangir, Pierre Tiako, Milkias Berhanu Tuka
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-22 (2024)
Abstract This study introduces an advanced mathematical methodology for predicting energy generation and consumption based on temperature variations in regions with diverse climatic conditions and increasing energy demands. Using a comprehensive data
Externí odkaz:
https://doaj.org/article/fbe4290568a04443aa031c603b099480
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:
De Los Reyes, Andres, author
Publikováno v:
Discrepant Results in Mental Health Research : What They Mean, Why They Matter, and How They Inform Scientific Practices, 2024, ill.
Externí odkaz:
https://doi.org/10.1093/oso/9780197686607.003.0010
Publikováno v:
International Journal of Manpower, 2024, Vol. 45, Issue 7, pp. 1350-1364.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJM-06-2023-0309
Publikováno v:
Sustainable Energy Research, Vol 11, Iss 1, Pp 1-14 (2024)
Abstract This study evaluated the performance of multiple models that used machine learning to anticipate wind speed in the city of Dhaka. The NASA Power website provided the data set for this investigation. The models used for prediction included th
Externí odkaz:
https://doaj.org/article/920ff9bf179d4265a1e03a080a23e1a4
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-23 (2024)
Abstract Bitumen, aggregate, and air void (VA) are the three primary ingredients of asphalt concrete. VA changes over time as a function of four factors: traffic loads and repetitions, environmental regimes, compaction, and asphalt mix composition. D
Externí odkaz:
https://doaj.org/article/f5d3683167024178a20067a874f651f0
Autor:
Ihab Mostafa Shaat, Alaa Alhamadani, Khafan Al-Shargi, Rashid Al-Habsi, Talal Al-Sedeiri, Asila Al Naabi, Asko Maki-Tanila
Publikováno v:
Agricultural and Food Science, Vol 33, Iss 3 (2024)
The growth curve parameters were estimated extending a linear regression to higher degree polynomial with attempts to use also the biologically appealing Gombertz function. The data contained monthly weight records from weaning to the age of 14 month
Externí odkaz:
https://doaj.org/article/18ffff58f65f4181b2174ac2de3eb206
Publikováno v:
Management Decision, 2024, Vol. 62, Issue 5, pp. 1560-1575.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/MD-05-2023-0867