A KECA identification method based on GA for E-nose data of six kinds of Chinese spirits

•Linear methods are difficult to obtain satisfactory results for identification of different kinds Chinese spirits.•KECA can solve nonlinear problems and has great potential in improving the identification ability of pattern recognition.•Matrix similarity measurement method and GA method are used to determine the optimal kernel parameter η.•Based on the GA method KECA + FDA detection model was availably constructed.•We think that the research results can provide a reference for improving the detection of complex samples by E​-nose. In order to improve the correct identification rate of six types of Chinese spirits using electronic nose (E-nose), the Kernel entropy component analysis (KECA) identification method combined with Genetic algorithm (GA) was proposed. Firstly, integral value (INV), relative steady-state average value (RSAV) and wavelet energy value (WEV) were extracted and employed to represent the E-nose data. Secondly, radial basis function (RBF) was selected as the kernel function, then the kernel parameter η of RBF was optimized by the matrix similarity measurement method and the GA. The corresponding optimized kernel parameter η was 16.8608 (matrix similarity measurement) and 67.9039 (GA), respectively. When the first 125 kernel entropy components were selected for Fisher discriminant analysis (FDA), the correct identification rate of FDA (KECA + FDA) combined with GA were 97.62 % and 98.81 % for the training set and testing set, respectively; the correct identification rate of FDA (KECA + FDA) combined with matrix similarity measurement were 93.58 and 91.67 % for the training set and testing set, respectively. Therefore, the kernel parameter η determined by GA was significantly better than that of matrix similarity measurement. Finally, the correct identification rate of FDA and KECA + FDA was compared, and the results of FDA were only 82.14 % and 79.92 % for the training set and testing set, respectively. The identification results of FDA were far worse than that of KECA + FDA. The KECA + FDA method combined with GA was suitable for the identification of the six types of Chinese spirits by E-nose.