Application of Four Intelligent Algorithms inPhase Equilibrium Data Fitting

Abstract The Marquardt-Levenberg(ML) algorithm is the most commonly used algorithm for phase equilibrium data fitting. However, this algorithm belongs to the local optimization algorithm. When ML algorithm was applied to multi-component system phase equilibrium data fitting, it is difficult to find the appropriate initial values for the general thermodynamic researchers owing to model parameters increasing sharply. In this paper, four kinds of intelligent algorithms, namely, genetic algorithm, neural network, annealing algorithm and particle swarm algorithm were applied to fitting the vapor-liquid equilibrium data of n-propanol (1)+acetonitrile (2) binary system by Wilson model and fitting the vapor-liquid equilibrium data of methanol (1)+acetonitrile (2)+1-ethyl-3-methylimidazolium tetrafluoroborate (3) ([EMIM] [BF₄]) ternary system by NRTL model, respectively. The mainly influencing factors of four algorithms on the phase equilibrium data fitting application were discussed. The results were also analyzed and compared. On the basis of above work, the scope of the application and the use of recommendations of each method were proposed.

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	Zhu Wei
	Liu bin
	Hou Haiyun
	Li Qing
	Wang Xinyuan
	Fan Zenglu

Keywords： phase equilibria； parameter estimation； genetic algorithm； neural networks； annealing algorithm； particle swarm algorithm

Received 2018-03-10;

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Zhu Wei, Liu bin, Hou Haiyun, Li Qing, Wang Xinyuan, Fan Zenglu.Application of Four Intelligent Algorithms inPhase Equilibrium Data Fitting[J] Chemcial Industry and Engineering, 2019,V36(4): 42-50

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