Parameter Optimization of Gas Purge-Microsyringe Extraction

Abstract

This paper proposes parameter optimization method of GP-MSE based on extraction parameters model. First, we identify the function relationship between dependent and independent variables by using neural networks. Second, independent variable set is made by interpolating the original independent variables, and then input these independent variables to fitted function to generate the dependent variable set. Last, we find the maximum value on dependent variable set to confirm the optimal parameters. Experimental result shows that the proposed method is not only simple and fast, but also ideal for recovery of single analyte.