چکیده مقاله
The Gibbs free energy of formation is very important property to predict the feasibility of chemical reactions, calculate equilibrium constants, and analyze reaction spontaneity In this work, a nonlinear group contribution based method was developed by combination of adaptive neuro fuzzy inference system ANFIS and group contributions GC methods In order to obtain simple and accurate model for prediction the gibbs free energy of formation of acid compounds, the genetic function approximation GFA method was used for selection the most important functional groups The required parameters of the models are the numbers of occurrences of three functional groups in each investigated acid molecule, which can be computed based on chemical structure of any acid molecule Using the ANFIS method the gibbs free energy of formation predicted with high accuracy and reliability that are quantified by the following statistical parameters: the squared correlation coefficient R² = 0 978, absolute average relative deviation percent AARD % =3 977, and the root mean squares error RMSE = 26 932 In general, the results obtained in this work showed that the ANFIS GC could be a promising machine learning approach to predict the gibbs free energy of formation, or possibly other physiochemical properties of acid compounds
کلیدواژهها
نویسندگان
Aboozar Khajeh
Department of Chemical Engineering, Birjand University of Technology, Birjand, Iran
شیوه ارجاع
Khajeh, Aboozar,1404,Adaptive neuro-fuzzy inference system (ANFIS) for prediction the gibbs energy of formation,The Second National Conference on Data Science in Engineering Applications,Tabriz
ارائهشده در
مجموعه مقالات دومین کنفرانس ملی علم داده در کاربردهای مهندسی17 مهر 1404 · تبریز