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
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;
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
DOI :
10.1109/CCDC.2009.5192402
