TY - GEN
T1 - A neural fuzzy system for soft computing
AU - Ciftcioglu, Ö
AU - Bittermann, M. S.
AU - Sariyildiz, I. S.
PY - 2007
Y1 - 2007
N2 - An innovative neural fuzzy system is considered for soft computing in design. A neural tree structure is considered with nodes of neuronal type, where Gaussian function plays the role of membership function. The total tree structure effectively works as a fuzzy logic system having system inputs and outputs. In the system, as result of special provisions, the locations of the Gaussian membership functions of non-terminal nodes happen to be unity, so that the system has several desirable features; it represents a fuzzy model maintaining the transparency and effectiveness while dealing with complexity. The research is described in detail and its outstanding merits are pointed out in a framework having transparent fuzzy modeling properties and addressing complexity issues at the same time. A demonstrative application of the model is presented from a demonstrative simple architectural design exercise and the favorable performance for similar applications is highlighted.
AB - An innovative neural fuzzy system is considered for soft computing in design. A neural tree structure is considered with nodes of neuronal type, where Gaussian function plays the role of membership function. The total tree structure effectively works as a fuzzy logic system having system inputs and outputs. In the system, as result of special provisions, the locations of the Gaussian membership functions of non-terminal nodes happen to be unity, so that the system has several desirable features; it represents a fuzzy model maintaining the transparency and effectiveness while dealing with complexity. The research is described in detail and its outstanding merits are pointed out in a framework having transparent fuzzy modeling properties and addressing complexity issues at the same time. A demonstrative application of the model is presented from a demonstrative simple architectural design exercise and the favorable performance for similar applications is highlighted.
UR - https://www.scopus.com/pages/publications/35148839505
U2 - 10.1109/NAFIPS.2007.383889
DO - 10.1109/NAFIPS.2007.383889
M3 - Conference contribution
AN - SCOPUS:35148839505
SN - 1424412145
SN - 9781424412143
T3 - Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS
SP - 489
EP - 495
BT - NAFIPS 2007
T2 - NAFIPS 2007: 2007 Annual Meeting of the North American Fuzzy Information Processing Society
Y2 - 24 June 2007 through 27 June 2007
ER -