TY - GEN
T1 - Building performance analysis supported by GA
AU - Ciftcioglu, Özer
AU - Sariyildiz, I. Sevil
AU - Bittermann, Michael S.
PY - 2007
Y1 - 2007
N2 - A neural tree structure is considered with nodes of neuronal type which is a Gaussian function and it plays the role of membership function. The total tree structure effectively works as a fuzzy logic system having system inputs and outputs. In this system the locations of the Gaussian membership functions of non-terminal nodes are unity so that the system has several desirable features and 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 modelling properties and addressing complexity issues at the same time. A demonstrative real-life application of this model is presented and the favourable performance for similar applications is highlighted.
AB - A neural tree structure is considered with nodes of neuronal type which is a Gaussian function and it plays the role of membership function. The total tree structure effectively works as a fuzzy logic system having system inputs and outputs. In this system the locations of the Gaussian membership functions of non-terminal nodes are unity so that the system has several desirable features and 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 modelling properties and addressing complexity issues at the same time. A demonstrative real-life application of this model is presented and the favourable performance for similar applications is highlighted.
KW - Analytical hierarchy process
KW - Fuzzy logic
KW - Knowledge model
KW - Neural tree
UR - http://www.scopus.com/inward/record.url?scp=80053170345&partnerID=8YFLogxK
U2 - 10.1109/CEC.2007.4424560
DO - 10.1109/CEC.2007.4424560
M3 - Conference contribution
AN - SCOPUS:80053170345
SN - 1424413400
SN - 9781424413409
T3 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
SP - 859
EP - 866
BT - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
T2 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007
Y2 - 25 September 2007 through 28 September 2007
ER -