Efficiency Evaluation for University Laboratory Based on Multi-layer SVM Classifier

In order to evaluate efficiency in university laboratory in a reasonable way, the index system for efficiency evaluation is established, and the efficiency class is separated into three classes-good, fair, and poor. To classify the efficiency of three classes, the evaluation model of multi-layer support vector machines (SVM) classifier is established. In order to verify the effectiveness of the method, 41 universities laboratories which are chosen from 211 project are used, and Levenberg-Marquardt neural network is also used to classify the same data and make comparison. The experiment results show that multi-layer SVM classifier is effective in efficiency evaluation for university laboratory when the training data set is not too much, and the method achieves better performance than Levenberg - Marquardt neural network.