Development of wavelet-based Kalman Online Sequential Extreme Learning Machine optimized with Boruta-Random Forest for drought index forecasting-Reference-Cited by-同舟云学术

Development of wavelet-based Kalman Online Sequential Extreme Learning Machine optimized with Boruta-Random Forest for drought index forecasting

Published:2023-01 Issue: Volume:117 Page:105545
ISSN:0952-1976
Container-title:Engineering Applications of Artificial Intelligence
language:en
Short-container-title:Engineering Applications of Artificial Intelligence

Author:

Jamei Mehdi,Ahmadianfar Iman,Karbasi Masoud,Malik Anurag,Kisi Ozgur,Yaseen Zaher Mundher

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering

Reference95 articles.

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2. Comparison of three different bio-inspired algorithms to improve ability of neuro fuzzy approach in prediction of agricultural drought, based on three different indexes;Aghelpour;Comput. Electron. Agric.,2020

3. A novel hybrid dragonfly optimization algorithm for agricultural drought prediction;Aghelpour;Stoch. Environ. Res. Risk Assess.,2021

4. Deep learning hybrid model with Boruta-Random forest optimiser algorithm for streamflow forecasting with climate mode indices, rainfall, and periodicity;Ahmed;J. Hydrol.,2021

5. LSTM integrated with boruta-random forest optimiser for soil moisture estimation under RCP4, 5 and RCP8. 5 global warming scenarios;Ahmed;Stoch. Environ. Res. Risk Assess.,2021

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