Repetitions
发表于 2025-3-28 15:49:41
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文艺
发表于 2025-3-28 19:08:33
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allergy
发表于 2025-3-28 23:13:13
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beta-cells
发表于 2025-3-29 06:54:03
2366-2557 built environment. This book is useful for the students, researchers, policy makers and professionals working in the area of civil engineering, climate change and disaster management.978-981-16-5503-6978-981-16-5501-2Series ISSN 2366-2557 Series E-ISSN 2366-2565
Duodenitis
发表于 2025-3-29 08:39:55
DDE Remediation and Degradation, impact, environmental impacts such as biodiversity, extinction of some fish species, and diminished reproductive capacity of livestock have been introduced. According to the confidence level of 95 percent and confidence interval of 10 percent, a field survey has been conducted for sample size 78. A
粘
发表于 2025-3-29 14:28:18
Lilia A. Albert,Francisco Badilloed with CC conditions, and extreme flood discharges (EFD), resulting from the 50, 100, and 1000 years return period estimation. Results showed that for the same flood river discharge, a water level variation from 13 to 40 cm is expected at the estuarine mouth, depending on the CC scenario. However,
Schlemms-Canal
发表于 2025-3-29 18:59:35
Lilia A. Albert,Francisco Badillontensive and requires good resolution meteorological, hydraulic, and topographical data sets. Therefore, the unavailability of long-term and reliable data sets in developing and underdeveloping countries cause a major hindrance for modelling in such catchments. The current study also adapts alternat
Afflict
发表于 2025-3-29 22:32:01
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法官
发表于 2025-3-30 01:39:35
https://doi.org/10.1007/978-1-4612-3810-2al simulations of the Saint Venant Equations for training and evaluation of the PINN model. The results demonstrate that the PINN model performs better than the ANN Models and is suitable for water depth forecasting.
Jejune
发表于 2025-3-30 06:45:14
https://doi.org/10.1007/978-1-4612-4362-5 against the prediction feature from the BN model. An evaluation of the hybrid (BN-ANN) model performance, in terms of suitable statistical measures, indicates good accuracy, affirming that BN is a promising tool for feature selection in multivariate hydrologic systems. Also, the predicted monthly r