In this paper, we propose a fuzzy neural network based on immune feedback learning (FNNBIFL) for the availability classifier of satellite images, which accelerates the learning speed, solves the problem of being trapped in the local minimum and improves the learning performance of fuzzy neural network. Using 122 satellite images, we compare the recognition results of the availability classifier trained by FNNBIFL or the traditional BP algorithm. Those results show that the recognition errors of FNNBIFL are reduced by 5.1%, and its learning speed is improved by 55%.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on availability of satellite images based on immune feedback learning fuzzy neural network


    Contributors:
    Zheng, Hong (author) / Wu, Xinghua (author) / Cao, Qiong (author)


    Publication date :

    2009


    Size :

    4 Seiten, 6 Quellen




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    An Optimal Fuzzy Neural Network Controller Based on Artificial Immune Principle

    Zuo, X.-q. / Li, S.-y. | British Library Online Contents | 2004


    Agricultural parcel localization on satellite images using U-Net-based neural network

    Pavlova, Maria / Savchik, Alexey / Teplyakov, Lev et al. | TIBKAT | 2020

    Free access

    A Nonlinear PID Controller Based on Fuzzy-Tuned Immune Feedback Law

    Ding, Y. | British Library Conference Proceedings | 2000


    Application of Fuzzy Neural Network Based on Immune Algorithm (IA) to AGC-ASC System

    Wang, F.-h. / Sun, Y.-k. / Wang, X.-p. | British Library Online Contents | 2004


    Investigation of cloud detecting for satellite images based on immune coding principle

    Hong, Z. / Qiong, C. / Yu, H. | British Library Online Contents | 2007