Monthly streamflow prediction using a hybrid stochastic-deterministic approach for parsimonious non-linear time series modeling

Monthly streamflow prediction using a hybrid stochastic-deterministic approach for parsimonious non-linear time series modeling

Accurate streamflow prediction is essential in reservoir management, flood control, and operation of irrigation networks. In this study, the deterministic and stochastic components of modeling are considered simultaneously. Two nonlinear time series models are developed based on autoregressive condi...

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Bibliographic Details
Main Authors: Zhen Wang, Nasrin Fathollahzadeh Attar, Keivan Khalili, Javad Behmanesh, Shahab S. Band, Amir Mosavi, Kwok-wing Chau
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
integrated hybrid models
nonlinear time series models
streamflow modeling
gene expression programming
urmia lake basin
stochastic and deterministic
Online Access:http://dx.doi.org/10.1080/19942060.2020.1830858

Internet

http://dx.doi.org/10.1080/19942060.2020.1830858

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