A Modeling of Vinyl Acetate Synthesis Process Based on Genetic Algorithm Optimization Neural Network

Abstract:

A chemical plant in vinyl acetate synthesis reaction as the object of study, based on site data collection and mechanism analysis to determine the auxiliary variables on the basis of on-site data processing, through a combination of genetic algorithms and neural network combined to build a synthetic reaction model. The genetic algorithm is introduced to take advantage of its good global search capability to reduce the risk of limited local optimal solution. At the same time, according to the characteristics of the neural network algorithm to avoid that training is too slow, resulting in not conducive to practical application. For this optimized BP Neural Network Based on Self-adapted Genetic Algorithm, by comparing the simulation data obtained by the instance of the digital signal proved that this method has better prospects than traditional neural network algorithm.

• Periodical: Advanced Materials Research (Volumes 765-767)
• Pages: 3115-3119
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.765-767.3115
• Online since: September 2013
• Authors: Hua Meng, Jie Zhu, Ming Yu Li
• Keywords: Genetic Algorithm (GA), Neural Network (NN), Optimization, Simulation

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