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The paper determines daily forecast demands for natural gas using artificial neural networks (MLPs). The influence of net-work structure, the type of activation function and the training process used on the quality of prediction were studied. It was found that the quality of forecasts was highly influenced by the network training algorithm. The smallest errors of the ex-pired forecasts (MAPE 5-6%)...
In this paper, two fuzzy Takagi-Sugeno models were built to describe daily gas consumption of rural households using the Gaussian and trapezoidal membership function. It was found that the predictive values of both models are similar and satis-factory (MAPE 5.3-5.5%) and slightly better than in the case of the model of neural network when the BFGS algorithm was used for training, as shown in the first...
The basic logistics tools of companies include forecasting. It plays an increasingly important role in gas companies with regard to the progressive liberalisation of the market. In the paper, there has been built a fuzzy relational model of daily natural gas demand of rural consumers, and it has served as an example to check the usefulness of such a model for short-term forecasting, supporting the...
Zapotrzebowanie odbiorców wiejskich na gaz ziemny opisano funkcją potęgową Cobba-Douglasa, w której zmiennymi objaśniającymi są liczba wiejskich odbiorców gazu i jego cena lub cena gazu ziemnego i dochód rozporządzalny wiejskich gospodarstw. Wyznaczone na podstawie opracowanych zależności prognozy wygasłe charakteryzują się małymi błędami, przy średnich absolutnych błędach prognoz ex post nie przekraczających...
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