Meta-Heuristic Algorithms for Hydrologic Frequency Analysis

Yousef Hassanzadeh (), Amin Abdi (), Siamak Talatahari () and Vijay Singh ()

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2011, vol. 25, issue 7, 1855-1879

Abstract: Meta-heuristic algorithms, such as the genetic algorithm and ant colony optimization, have received considerable attention in recent years due to their higher ability for solving difficult engineering optimization problems. This paper employs these techniques for estimating parameters of commonly used flood frequency distributions, and compares them with some conventional methods such as maximum likelihood, moments and probability weighted moments using annual maximum discharge data of 14 rivers from East-Azarbaijan, Iran. The results indicate that both the genetic algorithm and ant colony optimization are suitable parameter estimation alternatives. Also, the results of Monte Carlo simulation for various sample sizes, ranging from 20 to 100, demonstrate that the meta-heuristic algorithms yield accurate quantile estimates. Copyright Springer Science+Business Media B.V. 2011

Keywords: Hydrologic frequency analysis; Conventional methods; Meta-heuristic algorithms; Parameter estimation; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2011
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DOI: 10.1007/s11269-011-9778-1

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