|Table of Contents|

 The Method of Predicting the Rise of Temperature by
Combining Fuzzy System and Recursive Least Square
(PDF)

《哈尔滨理工大学学报》[ISSN:1007-2683/CN:23-1404/N]

Issue:
2017年06期
Page:
52-56
Research Field:
材料科学与工程
Publishing date:

Info

Title:
 The Method of Predicting the Rise of Temperature by
Combining Fuzzy System and Recursive Least Square
Author(s):
 WANG Gang ZHANG Bo WANG Guan YE San-pai
 ( Technology Center,Pinggao Group Co. ,Ltd. ,Pingdingshan 467001,China
Keywords:
 fitting the experiment of the rise of temperature fuzzy system regression analysis model
PACS:
TM11; TP18
DOI:
10. 15938 /j. jhust. 2017. 06. 010
Abstract:
 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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Last Update: 2018-03-10