Title :
Efficiency Evaluation for University Laboratory Based on Multi-layer SVM Classifier
Author :
Wang, Xiumei ; Cui, Yanbin ; Yang, Chenguang
Author_Institution :
North China Electr. Power Univ., Baoding
Abstract :
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.
Keywords :
educational institutions; laboratories; pattern classification; support vector machines; Levenberg-Marquardt neural network; index system; multi-layer SVM classifier; multi-layer support vector machines classifier; university laboratory efficiency evaluation; Laboratories; Mechanical engineering; Multi-layer neural network; Neural networks; Power system modeling; Statistical learning; Support vector machine classification; Support vector machines; Training data; Virtual colonoscopy;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.349
