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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiumei Wang Yanbin Cui Chenguang Yang |
| Copyright Year | 2007 |
| Description | Author affiliation: North China Electr. Power Univ., Baoding (Xiumei Wang) |
| 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. |
| Starting Page | 558 |
| Ending Page | 561 |
| File Size | 243747 |
| Page Count | 4 |
| File Format | |
| ISBN | 9780769528755 |
| DOI | 10.1109/ICNC.2007.349 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-24 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Support vector machines Virtual colonoscopy Laboratories Neural networks Statistical learning Support vector machine classification Training data Power system modeling Mechanical engineering Multi-layer neural network |
| Content Type | Text |
| Resource Type | Article |
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