Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Parameter estimation of water quality model using particle swarm optimization technique
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Darwinian rivers: evolving stream topographies to match hyporheic residence time distributions
Proceedings of the 14th annual conference on Genetic and evolutionary computation
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QUAL2Kw is a framework for the simulation of water quality in streams and rivers. Dynamic diel heat budget and water quality kinetics are calculated for one-dimensional steady-flow systems. The framework includes a genetic algorithm to facilitate the calibration of the model in application to particular waterbodies. The genetic algorithm is used to find the combination of kinetic rate parameters and constants that results in a best fit for a model application compared with observed data. The user has the flexibility to select any combination of parameters for the optimization and specify any appropriate function for goodness-of-fit.