Recognition of crude drugs based on SVM

Support Vector Machine (SVM) is a machine learning theory based on statistical learning algorithms, SVM based on kernel function has lots of unique advantages on solving the small sample, nonlinear and high dimensional pattern recognition. This article al so uses BP neural networks, Support Vector Machine based on PSO algorithm and so on to be compared to identify propolis in Yunnan. Compared with traditional algorithms, it can solve the small sample, nonlinear and other issues. The experiments show the performance is good when using SVM kernel function on solving the herbs recognition.