Auteur Farhad Gharagheizi
Documents disponibles écrits par cet auteur (17)
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Article : texte imprimé
Farhad Gharagheizi, Auteur ; Poorandokht Ilani-Kashkouli, Auteur ; Seyyed Alireza Mirkhani, Auteur |In this communication, a quantitative structure-property relationship (QSPR) is presented for an estimation of the upper flash point of pure compounds. The model is a multilinear equation that has eight parameters. All the parameters are solely [...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Poorandokht Ilani-Kashkouli, Auteur ; Amir H. Mohammadi, Auteur |The accuracy and predictability of predictive methods to determine the flammability characteristics of chemical compounds are of drastic significance in the chemical industry. This work aims at continuing application of the gene expression progr[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Ali Eslamimanesh, Auteur ; Sattari, Mehdi, Auteur |In this study, our objective is to apply the gene expression programming mathematical algorithm to propose a correlation based on the corresponding states method to determine the solubility parameters of 1641 pure compounds (mostly organic ones)[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Ali Eslamimanesh, Auteur ; Amir H. Mohammadi, Auteur |In this communication, an Artificial Neural Network―Group Contribution algorithm is applied to represent/predict the parachor of pure chemical compounds. To propose a reliable and predictive tool, 227 pure chemical compounds are investigated. Us[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Ali Eslamimanesh, Auteur ; Poorandokht Ilani-Kashkouli, Auteur |In the present study, a group contribution model is developed for determination of the vapor pressure of pure chemical compounds at temperatures from 55 to 3040 K. About 42 000 vapor pressure values belonging to around 1400 chemical compounds (m[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Behnam Tirandazi, Auteur ; Reza Barzin, Auteur |In the present work, a quantitative structure-property relationship (QSPR) study is performed to predict the aniline point temperature of pure hydrocarbon components. As a powerful tool, genetic algorithm-based multivariate linear regression ([...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Ali Eslamimanesh, Auteur ; Sattari, Mehdi, Auteur |In the present communication, we propose a corresponding states method for calculation/estimation of the vapor thermal conductivity of chemical compounds (mostly organic), applying the gene expression programming (GEP) algorithm. Around 16000 th[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Ali Eslamimanesh, Auteur ; Amir H. Mohammadi, Auteur |The determination of the solubility parameter of organic compounds has been of much significance in the chemical industry. In this study, we propose a predictive method based on the combination of the Group Contribution strategy with the Artific[...]
Article : texte imprimé
A new Neural network group contribution method for estimation of upper flash point of pure chemicals
Farhad Gharagheizi, Auteur ; Reza Abbasi, Auteur |In this study, a new group contribution-based model is presented for the prediction of the upper flash point temperature of pure compounds based on a large data set containing 1294 pure compounds. The model is a neural network using a number of [...]
Article : texte imprimé
Farhad Gharagheizi, Auteur |In the present study, a group contribution based neural network method is developed to predict the lower flammability limit temperature (LFLT) of pure compounds. The needed parameters of the model are the occurrences of 125 functional groups in [...]
Article : texte imprimé
Ali Eslamimanesh, Auteur ; Farhad Gharagheizi, Auteur ; Amir H. Mohammadi, Auteur |In this work, the group contribution (GC) method is coupled with the least-squares support vector machine (LSSVM) mathematical algorithm to develop a model for representation/prediction of the dissociation conditions of structure H (sH) clathrat[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Reza Abbasi, Auteur ; Behnam Tirandazi, Auteur |In this work, a new model is presented for estimation of Henry's law constant of pure compounds in water at 25 °C (H). This model is based on a combination between a group contribution method and neural networks. The needed parameters of the mod[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Sattari, Mehdi, Auteur |One of the industrially important thermodynamic properties of polymer solutions is the upper critical solution temperature at the limit of infinite chain length of polymers, which is used to realize the usage limits of polymer solutions; this pr[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Sattari, Mehdi, Auteur |A quantitative structure property relationship study was performed to develop a model for the prediction of triple-point temperature of pure components. For developing this model, 638 pure components were used, and, for whichever, 1664 molecular[...]
Article : texte imprimé
Farhad Gharagheizi, Auteur ; Omid Babaie, Auteur ; Sahar Mazdeyasna, Auteur |In this work, the artificial neural network-group contribution (ANN-GC) method is applied to estimate the vaporization enthalpy of pure chemical compounds at their normal boiling point. A group of 4907 pure compounds from various chemical famili[...]
