ARTIFICIAL NEURAL NETWORK PREDICTION FOR THERMAL DECOMPOSITION OF POTASSIUM NITRATE (KNO3) AND BENZOIC ACID (C6H5COOH)

作者：Beken Murat^*

来源：Modern Physics Letters B, 2010, 24(17): 1855-1868.

DOI：10.1142/S0217984910024213

• Differential thermal analysis (DTA)
• artificial neural networks (ANN)
• phase transitions
• enthalpy
• critical points
• C6H5COOH
• KNO3

The aim of this work is to correlate the results of experimental data by using the differential thermal analysis (DTA) method and predictions of artificial neural networks (ANNs). Thermal decomposition of potassium nitrate (KNO3) and benzoic acid (C6H5COOH) have been analyzed by the simultaneous DTA method. Kinetic parameters (critical points, the change of enthalpy) have been investigated. A computer model, based on multilayer feed-forwarding back-propagation is used for the prediction of critical points, phase transitions of potassium nitrate (KNO3) and benzoic acid (C6H5COOH). As a result of our study, we conclude that the ANN model shows a considerably good result about the prediction of experimental data.

• 出版日期2010-7-10