Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

New system identification technique using fuzzy regression analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Kaneyoshi, M. ; Hitach Zosen Corp, Osaka, Japan ; Tanaka, H. ; Kamei, M. ; Furuta, H.

A system identification method is developed, in which measured field data are assumed to be fuzzy data and fuzzy regression analysis is applied to the process of system identification. Although the method includes fuzzy coefficients in the formulation, it can be solved without difficulty by using a linear programming algorithm. This fuzzy system identification method has been applied to the construction of a cable-stayed bridge, the Shugahara-Shirokita Bridge in Osaka, Japan. The results confirm that the system identification technique proposed is not only simple to handle but also very practical, compared with previous methods

Published in:

Uncertainty Modeling and Analysis, 1990. Proceedings., First International Symposium on

Date of Conference:

3-5 Dec 1990