Neural networks application in managing the energy efficiency of industrial enterprise

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The article is devoted to the creation of a method for using of neural networks approach in solving problems of energy efficiency management at the industrial enterprise. The method allows to obtain an approximate expected value of the energy intensity of production, depending on the values of the main factors affecting it. The multilayer perceptron was chosen as the type of neural network, synthesis of which was carried out by using the genetic algorithm. When sampling for the synthesis of a neural network, we used the results that were obtained by means of a priori ranking, correlation and regression analysis based on the statistical data of industrial enterprises in machine-building profile. The recommendations of the use of the method and the application of its results in the practical implementation at the industrial enterprise are given. Calculations based on the aforementioned method ensured a high precision of prediction of energy intensity values for industrial enterprises that were included in the sample during the synthesis of the neural network, and an acceptable error while testing on industrial enterprises from a test sample.

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    • Рисунок 1. Нейронная сеть для управления энергоэффективностью предприятия
    • Рисунок 2. Сигмоидальная активационная функция
    • Рисунок 3. Процесс оптимизации весовых коэффициентов ИНС и сдвигов нейронов в программе Mendel4
    • Рисунок 4. Окно ввода-вывода данных в программе Mendel4
    • Таблица 1. Влияющие факторы и энергоемкость предприятий
    • Таблица 2. Значения входных и выходных данных