FLEET
发表于 2025-3-27 00:10:51
Daily Flood Forecasts with Intelligent Data Analytic Models: Multivariate Empirical Mode Decompositagnostic analysis and forecast error histograms further reveal that the MEMD-M5 tree has a greater resemblance to that of the observed data supporting the outcomes of statistical evaluation. Such advancements in flood prediction models, attained through data intelligent analytical methods, are very
疲劳
发表于 2025-3-27 04:17:57
Machine Learning Method in Prediction Streamflow Considering Periodicity Component,0.8 m./s for the Garhihabibullah, respectively. Including periodicity input (month number of the output) considerably improved the models’ efficiency in prediction monthly streamflow in both stations: improvements in the RMSEs of the optimal LSTM, ELM, and RF models were 20.8%, 20.5%, and 3.7 for th
大酒杯
发表于 2025-3-27 05:34:20
Empirical Model for the Assessment of Climate Change Impacts on Spatial Pattern of Water Availabiliom GPCC rainfall and CRU temperature. Finally, the multi-model ensemble mean projections of rainfall and temperature of four GCMs namely MRI-CGCM3, HadGEM2-ES, CSIRO-Mk3-6-0 and CESM1-CAM5 were used in the model for the assessment of climate change impact on water sustainability. The results reveale
guardianship
发表于 2025-3-27 12:44:31
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Anecdote
发表于 2025-3-27 15:25:49
Oluwatobi Aiyelokun,Gbenga Ogunsanwo,Akintunde Ojelabi,Oluwole Agbede
打折
发表于 2025-3-27 17:55:24
Anurag Malik,Anil Kumar,Sinan Q. Salih,Zaher Mundher Yaseen
聋子
发表于 2025-3-27 23:42:42
Ramendra Prasad,Dhrishna Charan,Lionel Joseph,Thong Nguyen-Huy,Ravinesh C. Deo,Sanjay Singh
藕床生厌倦
发表于 2025-3-28 04:27:51
Rana Muhammad Adnan,Mohammad Zounemat-Kermani,Alban Kuriqi,Ozgur Kisi
Exposure
发表于 2025-3-28 10:17:17
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Fecal-Impaction
发表于 2025-3-28 13:33:49
https://doi.org/10.1007/978-981-15-5772-9disaster risk management; artificial intelligence; machine learning algorithms; environmental sciences;