| Improved Ellipsoidal unit Neural Networks and Its Applications in CSTR |
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| 作者姓名： | ZHAO Xiang ZHOU Shao qi XIAO De yun |
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| 摘 要： | To overcome the limitations of the standard ellipsoidal unit neural networks, some new approaches used in ellipsoidal unit neural networks have been proposed. These new approaches address three main issues: firstly, to understand better and represent the nature of fault classification boundaries; secondly, to determine the network structure without the usual trial and error schemes; lastly, to avoid erroneous generalizations. The application in CSTR shows that the ellipsoidal unit networks can possess arbitrary nonlinear classifying ability, nonlinear interfacial describing ability, and obtain accurate and efficient diagnosis results.
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| 关 键 词： | fault diagnosis neural networks ellipsoidal unit clustering algorithm BP algorithm |
| 修稿时间： | 2002/1/25 0:00:00 |
Improved Ellipsoidal unit Neural Networks and Its Applications in CSTR |
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| ZHAO Xiang,ZHOU Shao qi,XIAO De yun.Improved Ellipsoidal unit Neural Networks and Its Applications in CSTR[J].Storage & Process,2002(5):58-63. |
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| Authors: | ZHAO Xiang ZHOU Shao qi XIAO De yun |
| |
| Abstract: | To overcome the limitations of the standard ellipsoidal unit neural networks, some new approaches used in ellipsoidal unit neural networks have been proposed. These new approaches address three main issues: firstly, to understand better and represent the nature of fault classification boundaries; secondly, to determine the network structure without the usual trial and error schemes; lastly, to avoid erroneous generalizations. The application in CSTR shows that the ellipsoidal unit networks can possess arbitrary nonlinear classifying ability, nonlinear interfacial describing ability, and obtain accurate and efficient diagnosis results. |
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| Keywords: | fault diagnosis neural networks ellipsoidal unit clustering algorithm BP algorithm |
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