Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Hamed Mirshekar"'
Publikováno v:
International Journal of Science and Engineering, Vol 5, Iss 2, Pp 1-8 (2013)
In this paper, a comprehensive mathematical model is developed based on the Feed-ForwardBack Propagation Artificial Neural Network (FFBP-ANN). The model is employed for thecalculation of Vapor Liquid Equilibria (VLE) of four CO2-containing binary mix
Externí odkaz:
https://doaj.org/article/f714b47d0f4946e2ab60cb7494ef41bc
Publikováno v:
Journal of Composite Materials. 54:363-378
In this study, the diameter of polyvinyl butyral nanofibers was modeled using response surface method based on three variables, at three levels of central composite design and particle swarm optimization-least squares support vector machine. Under op
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3f2d0d40e5bda899887a6f93edb44051
https://doi.org/10.1177/0021998319863126
https://doi.org/10.1177/0021998319863126
Publikováno v:
Journal of Molecular Liquids. 236:344-357
The objective of the present study is to develop a mathematical model based on the least square support vector machine to predict the surface tension of ionic liquids (ILs). Molecular weight, reduced temperature, reduced pressure, critical compressib
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::105969bcaa1aded36e0b1916f944721f
https://doi.org/10.1016/j.molliq.2017.04.039
https://doi.org/10.1016/j.molliq.2017.04.039
Publikováno v:
Chemical Engineering & Technology. 40:529-536
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::886f202cc772c6b39686e22d943e4c43
https://doi.org/10.1002/ceat.201400389
https://doi.org/10.1002/ceat.201400389
Publikováno v:
Colloid and Polymer Science. 295:421-432
The aim of present study is development of an accurate mathematical model for prediction of water activity in poly(ethylene glycol)-water solutions. The least square support vector approach (LSSVM) was implemented for this purpose. Four hundred thirt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef7f3f054552596ca46d3e58d457f132
https://doi.org/10.1007/s00396-017-4017-9
https://doi.org/10.1007/s00396-017-4017-9
Autor:
Mostafa Keshavarz Moraveji, Abdolhossein Hemmati-Sarapardeh, Bahram Nasernejad, Saeid Atashrouz, Hamed Mirshekar
Publikováno v:
Journal of Molecular Liquids. 224:648-656
Among all physicochemical properties of ionic liquids (ILs), thermal conductivity has less been investigated both experimentally and theoretically. In this regard, experimental investigations and predictive models for thermal conductivity of ionic li
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cc357d7e6bd2270a52e84207787c771b
https://doi.org/10.1016/j.molliq.2016.09.106
https://doi.org/10.1016/j.molliq.2016.09.106
Autor:
Bahram Nasernejad, Mostafa Keshavarz Moraveji, Abdolhossein Hemmati-Sarapardeh, Hamed Mirshekar, Saeid Atashrouz
Publikováno v:
Korean Journal of Chemical Engineering. 34:425-439
The main objective of this study was to develop soft computing approaches for prediction of physicochemical properties of IL mixtures including: density, heat capacity, thermal conductivity, and surface tension. The proposed models in this study are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::958e0abcb06ef84ebe741fdfb1bbce98
https://doi.org/10.1007/s11814-016-0271-7
https://doi.org/10.1007/s11814-016-0271-7
Autor:
Abdolhossein Hemmati-Sarapardeh, Saeid Atashrouz, Hadi Mokarizadeh, Hamed Mirshekar, Ahmad Mohaddes Pour
Publikováno v:
Journal of Molecular Liquids. 304:112771
In this study, the least square support vector machine (LSSVM) as a robust approach along with genetic algorithm (GA) was utilized for prediction of SO2 solubility in ionic liquids (ILs). The proposed model used the pressure, temperature, critical te
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14f421645839c42f308a171acb813e23
https://doi.org/10.1016/j.molliq.2020.112771
https://doi.org/10.1016/j.molliq.2020.112771
Publikováno v:
ISRN Chemical Engineering. 2013:1-11
Artificial neural network (ANN) technique has been applied for estimation of vapor-liquid equilibria (VLE) for eight binary refrigerant systems. The refrigerants include difluoromethane (R32), propane (R290), 1,1-difluoroethane (R152a), hexafluoroeth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5558c2e9af6c74da4031c45a889cbad1
https://doi.org/10.1155/2013/930484
https://doi.org/10.1155/2013/930484
Autor:
Hamed Mirshekar, Ebrahim Hosaini‐Alvand, Alireza Joorabloo, Mahmoud Parvazinia, Mohammad Taghi Khorasani
Publikováno v:
Journal of Applied Polymer Science. 134:45116
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17e00f29da30ae461f066715a37eadc3
https://doi.org/10.1002/app.45116
https://doi.org/10.1002/app.45116