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Meta-Heuristic Algorithms for Hydrologic Frequency Analysis
Authors:Yousef Hassanzadeh  Amin Abdi  Siamak Talatahari  Vijay P Singh
Affiliation:(1) Department of Mathematics, Faculty of Science, Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia;(2) UTM Razak School of Engineering and Advanced Technology, Universiti Teknologi Malaysia International Campus, 50300 Kuala Lumpur, Malaysia;(3) School of Mathematical Science, Faculty of Science and Technology, National University of Malaysia, 43600 Bangi, Selangor, Malaysia
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.
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