Title : ( Estimation of nonlinear parameters of the type 5 Muskingum model using SOS algorithm )
Authors: saeid khalifeh , Kazem Esmaili , Saeed Reza Khodashenas , Vahid Khalifeh ,
Full TextAbstract
The Symbiotic Organisms Search Algorithm (SOS) is used as an algorithm based on the social behavior of Symbiotic Organisms in optimization of Non-linear 5 model parameters for flood routing. The data used in this article is 4 day observations from 30 November 2008 to 3 December 2008, which is located between the Molasani, and Ahwaz station on the Karun River. The time series data used included river inflow, storage volume, and river outflow. The results of the developed model with the Symbiotic Organisms Search Algorithm (SOS) were compared with the other Evolutionary algorithms including Genetic Algorithm (GA, and Harmony Search Algorithm (HS). The analysis showed that the best solutions achieved from the objective function by the SOS, GA, and HS algorithms were 143052.02, 143252.35, and 142952.45, respectively. The processes of these datasets determined that the SOS algorithm was premiere to GA, and HS algorithms on the optimal flood routing river problem
Keywords
, Karun river, Non-linear, The symbiotic organisms search algorithm , Hydrologic model
@article{paperid:1081222,
author = {Khalifeh, Saeid and Esmaili, Kazem and Khodashenas, Saeed Reza and Vahid Khalifeh},
title = {Estimation of nonlinear parameters of the type 5 Muskingum model using SOS algorithm},
journal = {MethodsX},
year = {2020},
volume = {7},
month = {January},
issn = {2215-0161},
pages = {101040--1},
numpages = {-101039},
keywords = {Karun river; Non-linear; The symbiotic organisms search algorithm ;Hydrologic model},
}
%0 Journal Article
%T Estimation of nonlinear parameters of the type 5 Muskingum model using SOS algorithm
%A Khalifeh, Saeid
%A Esmaili, Kazem
%A Khodashenas, Saeed Reza
%A Vahid Khalifeh
%J MethodsX
%@ 2215-0161
%D 2020
