Application of artificial intelligence technologies to assess water salinity

Abstract Topical issues of developing theoretical and methodological tools for constructing a fuzzy logical model for assessing water salinity are considered. When constructing a Sugeno fuzzy logical model for estimating water salinity, a rational number of rules and effective values of their membership functions were chosen. Initially, the membership function parameters were obtained from water industry experts. In the future, it is necessary to adjust the parameters of the membership function using neural networks to obtain the minimum number of fuzzy rules.

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