2013
DOI: 10.1186/2228-5547-4-14
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Estimation of vapor pressures, compressed liquid, and supercritical densities for sulfur dioxide using artificial neural networks

Abstract: Homo-and copolymers of 2-(N-phthalimido)ethyl methacrylate (NPEMA) and p-chlorophenyl methacrylate (PCPMA) were prepared in N,N-dimethyl formamide (DMF) solution at 70 °C using 2,2-azo-bisisobutyronitrile (AIBN) as initiator. The nano-CdS-doped polymer composite of NPEMA and PCPMA was prepared via in situ technique. The homo-and copolymers of NPEMA and PCPMA were characterized using FT-IR spectroscopy and gel permeation chromatography (GPC). The polymer nano composites were characterized using FT-IR spectrosco… Show more

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“…The work showed that this method could estimate the density of hydrocarbons with good accuracy. In addition, Moghadassi et al [8] presented a model by a neural network that could estimate the sulfur dioxide density. The best network arrangement for this case was the Levenberg-Marquardt training algorithm with 15-10-1 topology and had good performance.…”
Section: *Correspondingmentioning
confidence: 99%
“…The work showed that this method could estimate the density of hydrocarbons with good accuracy. In addition, Moghadassi et al [8] presented a model by a neural network that could estimate the sulfur dioxide density. The best network arrangement for this case was the Levenberg-Marquardt training algorithm with 15-10-1 topology and had good performance.…”
Section: *Correspondingmentioning
confidence: 99%