TY - GEN
T1 - Optimal load allocations by linkage of evolutionary optimization algorithms with inductive models of watershed response
AU - Tufail, Mohammad
AU - Ormsbee, Lindell
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=37249032399&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=37249032399&partnerID=8YFLogxK
U2 - 10.1061/40792(173)349
DO - 10.1061/40792(173)349
M3 - Conference contribution
AN - SCOPUS:37249032399
SN - 0784407924
SN - 9780784407929
T3 - World Water Congress 2005: Impacts of Global Climate Change - Proceedings of the 2005 World Water and Environmental Resources Congress
SP - 349
BT - World Water Congress 2005
T2 - 2005 World Water and Environmental Resources Congress
Y2 - 15 May 2005 through 19 May 2005
ER -