Forecasting of the daily demand for natural gas in rural households using the methods of artificial intelligence. Part II. Forecasting using fuzzy logic

J. Małopolski; M. Trojanowska; K. Nęcka

2/2015 vol. 60

ORIGINAL PAPER

J. Małopolski ¹

M. Trojanowska ¹

K. Nęcka ¹

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University of Agriculture in Krakow, Department of Power Engineering and Agricultural Processes Automation, ul. Balicka 116B, 30-149 Kraków, Poland

Journal of Research and Applications in Agricultural Engineering 2015;60(2):65-67

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References (10)

KEYWORDS

natural gas

short-term forecasts

fuzzy logic

ABSTRACT

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 section of the study.

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