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    An intelligent approach for optimal prediction of gas deviation factor using particle swarm optimization and genetic algorithm

    , Article Journal of Natural Gas Science and Engineering ; Volume 14 , September , 2013 , Pages 132-143 ; 18755100 (ISSN) Chamkalani, A ; Mae'soumi, A ; Sameni, A ; Sharif University of Technology
    2013
    Abstract
    The measurement of PVT properties of natural gas in gas pipelines, gas storage systems, and gas reservoirs require accurate values of compressibility factor. Although equation of state and empirical correlations were utilized to estimate compressibility factor, but the demands for novel, more reliable, and easy-to-use models encouraged the researchers to introduce modern tools such as artificial intelligent systems.This paper introduces Particle swarm optimization (PSO) and Genetic algorithm (GA) as population-based stochastic search algorithms to optimize the weights and biases of networks, and to prevent trapping in local minima. Hence, in this paper, GA and PSO were used to minimize the... 

    Prediction of CO2-oil molecular diffusion using adaptive neuro-fuzzy inference system and particle swarm optimization technique

    , Article Fuel ; Volume 181 , 2016 , Pages 178-187 ; 00162361 (ISSN) Ejraei Bakyani, A. R ; Sahebi, H ; Ghiasi, M. M ; Mirjordavi, N ; Esmaeilzadeh, F ; Lee, M ; Bahadori, A ; Sharif University of Technology
    Elsevier Ltd 
    Abstract
    The quantification of carbon dioxide (CO2) dissolution in oil is crucial in predicting the potential and long-term behavior of CO2 in reservoir during secondary and tertiary oil recovery. Accurate predicting carbon dioxide molecular diffusion coefficient is a key parameter during carbon dioxide injection into oil reservoirs. In this study a new model based on adaptive neuro-fuzzy inference systems (ANFIS) is designed and developed for accurate prediction of carbon dioxide diffusivity in oils at elevated temperature and pressures. Particle Swarm Optimization (PSO) as population based stochastic search algorithms was applied to obtain the optimal ANFIS model parameters. Furthermore, a simple...