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In this paper, a cognitive analysis of the factors of the influence of heavy metals on the aquatic ecosystem is performed. Its purpose is to simplify and to improve the efficiency of further modeling process of the aquatic ecosystems under the heavy metals influence identification on the basis of a neural network. The analysis revealed the least important factors to ignore them in the simulation.
In this paper the authors have analyzed the heavy metals influence on the ichthyo fauna state and systematized it, classified the aquatic ecosystem states, developed the mathematical model for their identification based on a modified Perceptron, to create a functional and information-logical model of information system to study the heavy metals influence on the living organisms. The article presents...
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