DocumentCode
354214
Title
A kind of “growing” function link nets and its application in the prediction of oil field yield
Author
Weijian, Ren ; Guangyi, Chen ; Tienan, Liu ; Di, Yu ; Changjiang, Zhang
Author_Institution
Dept. of Autom. & Control Eng., Daqing Pet. Inst., Heilongjiang, China
Volume
2
fYear
2000
fDate
2000
Firstpage
1055
Abstract
A kind of new “growing” functional link nets prediction models and recursive Gauss-Newton learning algorithm are stated. These new networks and learning algorithm have the characteristics of fast learning and training speed and high prediction precision. They have been successfully applied to prediction problems of oil field yield. Validity of the new scheme is indicated
Keywords
Newton method; learning (artificial intelligence); neural nets; petroleum industry; growing function link nets; oil field yield; recursive Gauss-Newton learning algorithm; Automation; Control engineering; Intelligent control; Least squares methods; Neural networks; Newton method; Petroleum; Predictive models; Recursive estimation;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location
Hefei
Print_ISBN
0-7803-5995-X
Type
conf
DOI
10.1109/WCICA.2000.863398
Filename
863398
Link To Document