A Study of Applying Genetic Algorithm to Predict Reservoir Water Quality

This paper is aimed at demonstrating a genetic algorithm method and applying it to predict the water quality of reservoir in Taiwan island using remote sensing data. Genetic algorithms will be combined with operation tree (GAOT) to find the relationships between input and output data. A fittest function type will be obtained automatically from this method. The advantages of GA are global optimization, nonlinearity, flexibility and parallelism. In the current case study, GA is used to construct the relationship between algae concentration and Landsat sensor data. The results show that the model has better performance than the traditional LN transform of linear regression method, and similar performance compared with back-propagation neural network (BPNN) method.