Article ID Journal Published Year Pages File Type
6595732 Computers & Chemical Engineering 2014 46 Pages PDF
Abstract
A systematic optimization method based on combination of radial basis function neural network (RBF-NN) and genetic algorithm (GA) is developed for optimal design of DWC. The RBF-NN is built by a series of rigorous simulations of DWC for different sets of stage numbers with available simulation software. Then, GA is applied to optimize the stage numbers of the DWC with an objective (cost) function evaluated with the results obtained by the RBF-NN. As a simulation based approach, the proposed method shows its strength in finding the optimal solution by just evaluating small portion of the possible combinations of the stage numbers, and thus can be known as a promising method for optimal design of DWC. Three case studies were solved to detect the optimal structure and their sensitivity to operational conditions was analyzed. The results were shown encouraging compared with those found in the literature.
Related Topics
Physical Sciences and Engineering Chemical Engineering Chemical Engineering (General)
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