Gene expression programming strategy for estimation of flash point temperature of non-electrolyte organic compounds

Gharagheizi, Farhad; Ilani-Kashkouli, Poorandokht; Farahani, Nasrin; Mohammadi, Amir H.

doi:10.1016/j.fluid.2012.05.015

Cited by 40 publications

(25 citation statements)

References 24 publications

(36 reference statements)

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“…GEP is made of fitness function, terminal set, function set, termination condition, and control parameters, which are considered as the central elements of the GEP system. The outcomes generated by the GP technique exhibit tree topologies and are displayed in a functional programming language . It is important to note that the genetic operators perform on the chromosome level in the GEP method, which leads to an extreme simplification in the generation of genetic diversity .…”

Section: Theorymentioning

confidence: 99%

New efficient tool diagnoses asphaltene stability: Utilization of refractive index

Ahmadi

Zendehboudi

2019

Can J Chem Eng

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Asphaltene precipitation/deposition is considered a critical issue in the petroleum industry as it causes damages and blockage in various process equipment (e.g., pipe, pump, and vessel) and porous formation. To prevent this obstruction, it seems necessary to attain a reasonable estimate of the precipitation time, in other words, the time of asphaltene stability in crude oils. The gene expression programming (GEP) technique is utilized in this study to develop a correlation for the prediction of this important parameter using real refractive index (RI) data. The independent variables considered for the development of the correlation are the composition of aromatics, saturates, and resins in weight percentage. The predicted outputs show a better match with the real data, compared to the results obtained from other available predictive tools and/or correlations. Besides its simplicity, the developed correlation can have a broad range of applications in oil production plants in order to ensure that proper strategies are determined to avoid asphaltene precipitation/deposition throughout various stages of oil production and processing.

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Section: Theorymentioning

confidence: 99%

New efficient tool diagnoses asphaltene stability: Utilization of refractive index

Ahmadi

Zendehboudi

2019

Can J Chem Eng

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“…In spite of GP method, encoded linear chromosomes represent population individuals in which these chromosomes will be translated into the genotype and phenotype. These elements are known as expression parse trees . So, the ET and chromosome are the main components of GEP mathematical strategy.…”

Section: Gene Expression Programmingmentioning

confidence: 99%

Toward gene expression programming for accurate prognostication of the critical oil flow rate through the choke: correlation development

Rostami

Ebadi

2017

Asia-Pacific J Chem Eng

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In this study, gene expression programming (GEP) was employed to develop a new equation for calculating choke flow rate as a function of fluid properties and wellhead choke characteristics. For this reason, a comprehensive databank was adopted from the petroleum industry, and then, the databank was split into three groups of training set for model construction (70% of database), test set for model evaluation (15% of database), and validation set for avoiding over‐fitting problem (15% of database). For assessing of GEP model, numerous statistical and graphical tools were applied, and then, it was compared with widely applied literature correlations. Consequently, the proposed tool in this study gives the best fit with the actual flow rate data with the average absolute relative deviation of 11.0872% and determination coefficient (R2) of 0.9695. Additionally, cumulative frequency plot demonstrates that the GEP model has the highest frequency over the database. The outcomes of the GEP model were also compared with the outputs of the artificial neural network (ANN) revealing the higher precision of the ANN than the proposed GEP model in this study. At the end, it is worthwhile that the suggested model can be used as reliable tool for choke performance modeling. © 2017 Curtin University and John Wiley & Sons, Ltd.

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“…While the GA utilizes encoded numbers as solutions for a problem, GP uses parse trees to characterize the solution for problem under consideration . Hence, in GP method the members of populations the are candidate solutions for a problem are symbolic expression trees (ETs) . In GEP method, these individual solutions are in the form of linear chromosomes that will be transferred into appropriate ET form as the modeling process proceeds.…”

Section: Overview Of Gene Expression Programmingmentioning

confidence: 99%

Accurate model based on artificial intelligence for prediction of carbon dioxide solubility in aqueous tetra‐n‐butylammonium bromide solutions

Hoseinpour

Barati-Harooni

Nadali

et al. 2017

Journal of Chemometrics

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This study highlights the application of radial basis function (RBF) neural networks, adaptive neuro‐fuzzy inference systems (ANFIS), and gene expression programming (GEP) in the estimation of solubility of CO2 in aqueous solutions of tetra‐n‐butylammonium bromide (TBAB). The experimental data were gathered from a published work in literature. The proposed RBF network was coupled with genetic algorithm (GA) to access a better prediction performance of model. The structure of ANFIS model was trained by using hybrid method. The input parameters of the model were temperature, pressure, mass fraction of TBAB in feed aqueous solution (wTBAB), and mole fraction of TBAB in aqueous phase (xTBAB). The solubility of CO2 (xCO2) was the output parameter. Statistical and graphical analyses of the results showed that the proposed GA‐RBF, Hybrid‐ANFIS, and GEP models are robust and precise in the estimation of literature solubility data.

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Gene expression programming strategy for estimation of flash point temperature of non-electrolyte organic compounds

Cited by 40 publications

References 24 publications

New efficient tool diagnoses asphaltene stability: Utilization of refractive index

New efficient tool diagnoses asphaltene stability: Utilization of refractive index

Toward gene expression programming for accurate prognostication of the critical oil flow rate through the choke: correlation development

Accurate model based on artificial intelligence for prediction of carbon dioxide solubility in aqueous tetra‐n‐butylammonium bromide solutions

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