DocumentCode
2791900
Title
Research of buildings reliability evaluation model base on fuzzy neural network
Author
Lan, Li ; Ying-jie, Zhu ; Xue-qin, Qiu ; Zheng-lei, Li
Author_Institution
Coll. of Comput. Eng., Qingdao Technol. Univ., Qingdao, China
fYear
2009
fDate
17-19 June 2009
Firstpage
4365
Lastpage
4368
Abstract
In this paper, a novel model integrating genetic algorithm and fuzzy neural network was proposed to solve the problem of buildings performance assessment. buildings reliability assessment is a critical component of any building evaluation system (BES) decision-making process. Genetic algorithm was to optimize the connection weights of fuzzy neural network to acquire approximate optimal solution, and fuzzy neural network tuned finely further. The results show that more scientific, effective, accurate assessment of building performance can be acquired with genetic.algorithm-based fuzzy neural network model.
Keywords
decision making; fuzzy set theory; genetic algorithms; neural nets; reliability; structural engineering computing; building evaluation system decision-making process; buildings performance assessment; buildings reliability assessment; buildings reliability evaluation model; fuzzy neural network; model integrating genetic algorithm; Artificial neural networks; Computer network reliability; Convergence; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Genetic algorithms; Neural networks; Power system reliability; Predictive models; buildings reliability; evaluation model; genetic algorithm; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location
Guilin
Print_ISBN
978-1-4244-2722-2
Electronic_ISBN
978-1-4244-2723-9
Type
conf
DOI
10.1109/CCDC.2009.5192402
Filename
5192402
Link To Document