所蔵: Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models

Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models

Agriculture, meteorological, and hydrological drought is a natural hazard which affects ecosystems in the central India of Maharashtra state. Due to limited historical data for drought monitoring and forecasting available in the central India of Maharashtra state, implementing machine learning (ML)...

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主要な著者:	Elbeltagi A., Pande C.B., Kumar M., Tolche A.D., Singh S.K., Kumar A., Vishwakarma D.K.
その他の著者:	57204724397
フォーマット:	論文
出版事項:	Springer Science and Business Media Deutschland GmbH 2024
主題:	Drought Machine learning Random forest (RF) Standardized precipitation index (SPI) Algorithms Droughts Ecosystem India Random Forest Maharashtra drought Gaussian method geographical region machine learning meteorology precipitation (climatology) regression analysis algorithm ecosystem random forest
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Prediction of meteorological drought and standardized precipitation index based on the random forest (RF), random tree (RT), and Gaussian process regression (GPR) models

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