Title :
Digital resources serving performance assessing based on fuzzy neural networks
Author :
Zhu, Shiwei ; Zhao, Yanqing ; Yu, Junfeng ; Wang, Lei ; Wei, Moji ; Wang, Aiping
Author_Institution :
Information research institute of Shandong Academy of Sciences, Jinan, China
Abstract :
This paper is innovatively to develop a new hybrid performance evaluation method in the literature of assessing the digital resources serving performances. The proposed method employs the hierarchical evaluation method based on fuzzy rules and artificial neural networks. The proposed method integrates the fuzzy logic and the artificial neural networks, which overcomes the shortcomings of redundant fuzzy rules. The evaluation index system is determined based on the universal principle and the research fruits of the former scholars home and abroad. We build a fuzzy neural network evaluation model to achieve the final evaluation goal of the digital resources. In addition, to evaluate the performance of the proposed approach, we compare its results with GRA-BPN model. The experimental results demonstrated that the proposed approach has higher accuracy and execution efficiency.
Keywords :
Indexes; BP networik; digital resources; fuzzy logic; nueral network; serving performance evaluation;
Conference_Titel :
Granular Computing (GrC), 2012 IEEE International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4673-2310-9
DOI :
10.1109/GrC.2012.6468638