Methods of neural networks for estimation of superficial water.S quality by usage of hydrobiological exponents

The experience of imitation neural networks using for creating models of casual connection of freshwater reservoir.s quality with structure and functional characteristics of water ecosystem is presented. There are examples of different configuration.s network training for estimation of water quality. The genetic algorithm for separation of taxonomical groups of zoobenthos, which are indicators of reservoir.s state is described.