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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Fan Bo Dong Ming Zhao Jie Zhang Qiang |
| Copyright Year | 2010 |
| Description | Author affiliation: The Missile College, Air Force Engineering University, Shan xi, San yuan, China (Fan Bo; Dong Ming; Zhao Jie; Zhang Qiang) |
| Abstract | The problem that how to use hierarchical genetic algorithm to determine the structure and parameters of neural networks was studied. Utilized the two grade coding structure of the hierarchical genetic algorithm to solve the ancient problem that when optimize the neural networks' structure, connection weights, threshold at the same time, the efficiency was low. Furthermore, an improved adaptive hierarchical genetic algorithm was educed, and it improved the shortage of the normal adaptive hierarchical genetic algorithm. At last, the improved adaptive genetic algorithm is used to the fault diagnosis of three-phase inverter, the simulation result shown the method was correct and applied. |
| File Size | 810035 |
| File Format | |
| ISBN | 9781424472352 |
| e-ISBN | 9781424472376 |
| DOI | 10.1109/ICCASM.2010.5622135 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-22 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Fault diagnosis Neural networks Hierarchical genetic algorithm Three-phase SPWM inverter |
| Content Type | Text |
| Resource Type | Article |
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