DocumentCode :
2689415
Title :
Building performance analysis supported by GA
Author :
Ciftcioglu, Özer ; Sariyildiz, I. Sevil ; Bittermann, Michael S.
Author_Institution :
Delft Univ. of Technol., Delft
fYear :
2007
fDate :
25-28 Sept. 2007
Firstpage :
859
Lastpage :
866
Abstract :
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.
Keywords :
Gaussian processes; fuzzy logic; neural nets; Gaussian function; Gaussian membership functions; demonstrative real-life application; fuzzy logic system; neural tree structure; neuronal type; nonterminal nodes; transparent fuzzy modelling; Evolutionary computation; Performance analysis; Nueral tree; analytical hierarchy process; fuzzy logic; knowledge model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
Type :
conf
DOI :
10.1109/CEC.2007.4424560
Filename :
4424560
Link To Document :
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