SENSITIVITY ANALYSIS OF HIERARCHICAL HYBRID FUZZY - NEURAL NETWORK

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic

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VOLUME 8 , ISSUE 3 (September 2015) > List of articles

SENSITIVITY ANALYSIS OF HIERARCHICAL HYBRID FUZZY - NEURAL NETWORK

Xing Haihua / Yu Xianchuan / Hu Dan / Dai Sha

Keywords : Hierarchical hybrid fuzzy - neural network, Sensitivity analysis, Differential method, Takagi- Sugeno model, Triangular membership function.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 8, Issue 3, Pages 1,837-1,854, DOI: https://doi.org/10.21307/ijssis-2017-832

License : (CC BY-NC-ND 4.0)

Received Date : 15-April-2015 / Accepted: 12-July-2015 / Published Online: 01-September-2015

ARTICLE

ABSTRACT

To identify the important attributes of complex system, which is high-dimensional and contain both discrete and continuous variables, this paper proposes a sensitivity analysis method of hierarchical hybrid fuzzy - neural network. We derive the sensitivity indexes of discrete and continuous variables through the differential method. To verify the effectiveness of our method, this study employed a man-made example and a remote sensing image classification example to test the performance of our method. The results show that our method can really identify the important variables of complex system and discover the relations between input and output variables; therefore, they can be applied to simplify the model and improve the classification accuracy of model.

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