@inproceedings{581a261e329749a98fce304c9b081eab,
title = "Building performance analysis supported by GA",
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 = "Analytical hierarchy process, Fuzzy logic, Knowledge model, Neural tree",
author = "{\"O}zer Ciftcioglu and Sariyildiz, \{I. Sevil\} and Bittermann, \{Michael S.\}",
year = "2007",
doi = "10.1109/CEC.2007.4424560",
language = "English",
isbn = "1424413400",
series = "2007 IEEE Congress on Evolutionary Computation, CEC 2007",
publisher = "IEEE Computer Society",
pages = "859--866",
booktitle = "2007 IEEE Congress on Evolutionary Computation, CEC 2007",
address = "United States",
note = "2007 IEEE Congress on Evolutionary Computation, CEC 2007 ; Conference date: 25-09-2007 Through 28-09-2007",
}