Fuzzy Regression Analysis as a Means of Estimating Electric Power Losses

V.Z. Manusov and A.V. Mogilenko (Russia)


Fuzzy regression, fuzzy logic, fuzziness, electric power losses, membership function


For a development of models with fuzzy initial information Tanaka, Chang and others offered and developed fuzzy regression analysis. In usual regression analysis an error between values obtained by regression model and observable data is considered as an error of observation, which is a random variate (with normal distribution and average of distribution equal to zero). In fuzzy regression analysis the same errors are considered caused by fuzziness of a model. The authors carried out researches on application of all methods of the fuzzy regression analysis in the problem of the electric power loss analysis in electrical networks and in the problems of electric power industry as a whole.

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