Application of optimized support vector machine in HACCP classification of fresh-cut lettuce processing

An automatic CCPs (critical control points) identification method for lettuce’s fresh-cut processing HACCP (hazard analysis and critical control point) implementation based on optimized SVM (support vector machine) model was introduced. The CCPs identification tests which use the general SVM algorithm showed its weakness because of the man-made kernel selection and the classification results had larger fluctuation. Generic algorithm was used to obtain an optimized kernel function and then the GA-SVM model was proposed. The model had been applied in the CCPs identification of lettuce’s fresh-cut processing and the classification accuracy of 87.5% was stabler than the traditional method. The method is also general which can be easily popularized to other HACCP implementations.