Application of Gaussian process regression to forecast multi-step ahead SPEI drought index
Forecasting of drought can be very useful in preparing to reduce its impacts, especially in the agricultural sector. Three machine learning models of MLP neural network, GRNN neural network, and Gaussian process regression were used to forecast the annual drought index (SPEI12) in intervals of 1 to...
Main Authors: | Porya Ghasemi, Masoud Karbasi, Alireza Zamani Nouri, Mahdi Sarai Tabrizi, Hazi Mohammad Azamathulla |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2021-12-01
|
Series: | Alexandria Engineering Journal |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016821002647 |
Similar Items
-
SPEI-Based Approach to Agricultural Drought Monitoring in Vojvodina Region
by: Jovana Bezdan, et al.
Published: (2019-07-01) -
Temporal and Spatial Variability of Drought Based on SPEI Analysis in Southeastern Romania
by: Alexandra CHELU, et al.
Published: (2020-03-01) -
Trends and variability of drought in the extended part of Chhota Nagpur plateau (Singbhum Protocontinent), India applying SPI and SPEI indices
by: Biswajit Bera, et al.
Published: (2021-12-01) -
Regionalization Analysis of SPI and SPEI Drought Indices for Karoon Basin
by: M. Saeidipour, et al.
Published: (2019-09-01) -
Estimation of SPEI Meteorological Drought Using Machine Learning Algorithms
by: Ali Mokhtar, et al.
Published: (2021-01-01)