Application of Fuzzy C-means algorithm as a novel approach to forecast gas density in different conditions

One of the dominant parameters in accurate calculation and forecasting processes gas industries is accurate estimation of gas properties. The gas density is known as an effective parameter in gas processes calculations which affected by pressure and temperature. In the present paper, the Fuzzy c-means (FCM) algorithm is utilized as a novel predictive tool to estimate gas density as function of molecular weight, critical pressure and critical temperature of gas, pressure and temperature. In the purpose of training and testing of proposed FCM algorithm, a total number of 1240 measured data were gathered from reliable sources. The outputs of model and experimental data comparisons showed the great agreement between them such that the coefficients of determination for training and testing datasets were determined as 0.9982 and 0.9903 respectively. According to the obtained results from the graphical and statistical comparisons it can be concluded that the FCM algorithm has great ability and enough accuracy in prediction of gas density.