• 中国精品科技期刊
  • CCF推荐A类中文期刊
  • 计算领域高质量科技期刊T1类
Advanced Search
Gu Xiaoqing, Wang Shitong. Knowledge Embedded Bayesian MA Fuzzy System[J]. Journal of Computer Research and Development, 2017, 54(5): 998-1011. DOI: 10.7544/issn1000-1239.2017.20160011
Citation: Gu Xiaoqing, Wang Shitong. Knowledge Embedded Bayesian MA Fuzzy System[J]. Journal of Computer Research and Development, 2017, 54(5): 998-1011. DOI: 10.7544/issn1000-1239.2017.20160011

Knowledge Embedded Bayesian MA Fuzzy System

More Information
  • Published Date: April 30, 2017
  • The most distinctive characteristic of fuzzy system is its high interpretability. But the fuzzy rules obtained by classical cluster based fuzzy systems commonly need to cover all features of input space and often overlap each other. Specially, when facing the high-dimension problem, the fuzzy rules often become more sophisticated because of too much features involved in antecedent parameters. In order to overcome these shortcomings, based on the Bayesian inference framework, knowledge embedded Bayesian Mamdan-Assilan type fuzzy system (KE-B-MA) is proposed by focusing on the Mamdan-Assilan (MA) type fuzzy system. First, the DC (dont care) approach is incorporated into the selection of fuzzy membership centers and features of input space. Second, in order to enhance the classification performance of obtained fuzzy systems, KE-B-MA learns both antecedent and consequent parameter of fuzzy rules simultaneously by a Markov chain Monte Carlo (MCMC) method, and the obtained parameters can be guaranteed to be global optimal solutions. The experimental results on a synthetic dataset and several UCI machine datasets show that the classification accuracy of KE-B-MA is comparable to several classical fuzzy systems with distinctive ability of providing explicit knowledge in the form of interpretable fuzzy rules. Rather than being rivals, fuzziness in KE-B-MA and probability can be well incorporated.
  • Related Articles

    [1]Li Xinran, Li Rongshou, Qin Chuan, Qian Zhenxing, Zhang Xinpeng. Generative Information Hiding Method Based on Couplet Carrier[J]. Journal of Computer Research and Development, 2025, 62(3): 779-789. DOI: 10.7544/issn1000-1239.202330663
    [2]Wang Shuo, Wang Jianhua, Tang Guangming, Pei Qingqi, Zhang Yuchen, Liu Xiaohu. Intelligent and Efficient Method for Optimal Penetration Path Generation[J]. Journal of Computer Research and Development, 2019, 56(5): 929-941. DOI: 10.7544/issn1000-1239.2019.20190012
    [3]He Yanxiang, Chen Yong, Wu Wei, Xu Chao, Li Qingan. Bus-Invert Encoding Oriented Low Power Scheduling Method[J]. Journal of Computer Research and Development, 2014, 51(8): 1773-1780. DOI: 10.7544/issn1000-1239.2014.20130066
    [4]Wang Changjing, Luo Haimei, Zuo Zhengkang. Formal Software Specification Generation Approach Based on Problem Patterns[J]. Journal of Computer Research and Development, 2013, 50(2): 352-360.
    [5]Wang Weizheng, Kuang Jishun, You Zhiqiang, Liu Peng. A Low-Power and Low-Cost BIST Scheme Based on Capture in Turn of Sub-Scan Chains[J]. Journal of Computer Research and Development, 2012, 49(4): 864-872.
    [6]Luo Zuying, Pan Yuedou. Transistor-Level Methodology on Power Optimization for CMOS Circuits[J]. Journal of Computer Research and Development, 2008, 45(4): 734-740.
    [7]Zhou Hongwei, Zhang Chengyi, and Zhang Minxuan. A Method of Statistics-Based Cache Leakage Power Estimation[J]. Journal of Computer Research and Development, 2008, 45(2): 367-374.
    [8]Wen Dongxin, Yang Xiaozong, and Wang Ling. A High Level Synthesis Scheme and Its Realization for Low Power Design in VLSI[J]. Journal of Computer Research and Development, 2007, 44(7): 1259-1264.
    [9]Ma Zhiqiang, Ji Zhenzhou, and Hu Mingzeng. A Low Power Data Cache Design Based on Very Narrow-Width Value[J]. Journal of Computer Research and Development, 2007, 44(5): 775-781.
    [10]Ma Zhiqiang, Ji Zhenzhou, and Hu Mingzeng. A Low-Power Instruction Cache Design Based on Record Buffer[J]. Journal of Computer Research and Development, 2006, 43(4): 744-751.

Catalog

    Article views (1069) PDF downloads (724) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return