The Method of Predicting the Ｒise of Temperature by Combining Fuzzy System and Ｒecursive Least Square
For the problem that the rise of temperature of fitting is too high to control，a new method of predicting the rise of temperature has been put forward. The training data and the testing data are obtained from the experiment of rising of temperature. Through training data，the fuzzy system is traine...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2017-12-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1453 |
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| Summary: | For the problem that the rise of temperature of fitting is too high to control，a new method of
predicting the rise of temperature has been put forward. The training data and the testing data are obtained from the
experiment of rising of temperature. Through training data，the fuzzy system is trained by recursive least square
combined genetic algorithm. Then the model is tested by testing data. The error is in reasonable range. The result
shows that the new method is feasible to predict the rise of temperature of connection fitting. Ｒegression analysis is
used to predict the rise of temperature of connection fitting and the result is compared with that of new model，the
result of new model is better than that of traditional regression analysis model，the result of comparison reflects that
the new method has advantages for predicting the rise of temperature. |
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| ISSN: | 1007-2683 |