title: QSPR prediction of flash point of esters by means of GFA and ANFIS.
abstract: A quantitative structure property relationship (QSPR) study was performed to develop a model for prediction of flash point of esters based on a diverse set of 95 components. The most five important descriptors were selected from a set of 1124 descriptors to build the QSPR model by means of a genetic function approximation (GFA). For considering the nonlinear behavior of these molecular descriptors, adaptive neuro-fuzzy inference system (ANFIS) method was used. The ANFIS and GFA squared correlation coefficient for testing set was 0.969 and 0.965, respectively. The results obtained showed the ability of developed GFA and ANFIS for prediction of flash point of esters.
authors.affiliation: Islamic Azad University, Birjand Branch, Birjand, Southern Khorasan, Iran.
authors.forename: Aboozar
authors.initials: A
authors.lastname: Khajeh
authors.forename: Hamid
authors.initials: H
authors.lastname: Modarress
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D004952:Esters / Q000737:chemistry*; D005390:Fires; D017143:Fuzzy Logic; D005823:Genetics / Q000706:statistics & numerical data*; D015233:Models, Statistical; D016571:Neural Networks, Computer; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D014835:Volatilization
chemical_list: D004952:Esters