Optimal load allocations by linkage of evolutionary optimization algorithms with inductive models of watershed response

Mohammad Tufail, Lindell Ormsbee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Two separate optimization strategies (genetic algorithm and box complex method) are compared in the development of optimal nutrient load allocations for the water quality-impaired Beargrass Creek Watershed in Louisville, Jefferson County, Kentucky. The optimal load allocations are determined by linking the optimization algorithms with receiving water inductive models developed for the lower reaches of the watershed. The inductive models are developed from (1) a synthesis of both input and output response variables as derived from a continuous simulation of the watershed using a calibrated HSPF model, and (2) a synthesis of the continuous and discrete water quality data sampled over the last 2 years in the watershed. Inductive model construction is performed by use of artificial neural networks and the use of functional fixed-set genetic programming. The use of inductive models provides a more computational efficient framework for linkage with an optimization model for use in developing an optimal loading strategy. Copyright ASCE 2005.

Original languageEnglish
Title of host publicationWorld Water Congress 2005
Subtitle of host publicationImpacts of Global Climate Change - Proceedings of the 2005 World Water and Environmental Resources Congress
Pages349
Number of pages1
DOIs
StatePublished - 2005
Event2005 World Water and Environmental Resources Congress - Anchorage, AK, United States
Duration: May 15 2005May 19 2005

Publication series

NameWorld Water Congress 2005: Impacts of Global Climate Change - Proceedings of the 2005 World Water and Environmental Resources Congress

Conference

Conference2005 World Water and Environmental Resources Congress
Country/TerritoryUnited States
CityAnchorage, AK
Period5/15/055/19/05

ASJC Scopus subject areas

  • Water Science and Technology

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