Application of multi-agent genetic algorithm to parameter estimation of Muskingum Model

The ability of apperception and counteractive to environment of agent is combined with searching mode of genetic algorithm to establish an improved multi-agent algorithm for estimating the parameter of Muskingum Model.In this model every agent represents an optional solution and is fixed in the grid.In order to elevate its self energy every agent competes or cooperates with its neighbors,and it can also use its knowledge to study for elevating the energy.Through the interaction between the agents the objective of optimizing the parameters can be realized.The advantage of this proposed method is demonstrated by an example.