Browsing by Author "Yang, Longzhi"

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  • Yang, Longzhi; Shen, Qiang (2011-12-12)
    Fuzzy interpolative reasoning strengthens the power of fuzzy inference by the enhancement of the robustness of fuzzy systems and the reduction of the systems’ complexity. However, after a series of interpolations, it is ...
  • Shen, Qiang; Yang, Longzhi (2010-07-27)
    Adaptive fuzzy interpolation strengthens the potential of fuzzy interpolative reasoning owning to its efficient identification and correction of defective interpolated rules during the interpolation process [11]. This ...
  • Shen, Qiang; Yang, Longzhi (2010-07)
    Adaptive fuzzy interpolation strengthens the potential of fuzzy interpolative reasoning owning to its efficient identification and correction of defective interpolated rules during the interpolation process [11]. This ...
  • Shen, Qiang; Yang, Longzhi (2011-09-26)
    Adaptive fuzzy interpolation strengthens the potential of fuzzy interpolative reasoning. It first identifies all possible sets of faulty fuzzy reasoning components, termed the candidates, each of which may have led to all ...
  • Shen, Qiang; Yang, Longzhi (IEEE Press, 2011-09-26)
    Adaptive fuzzy interpolation strengthens the potential of fuzzy interpolative reasoning. It first identifies all possible sets of faulty fuzzy reasoning components, termed the candidates, each of which may have led to all ...
  • Shen, Qiang; Yang, Longzhi (2011-09-26)
    Adaptive fuzzy interpolation strengthens the potential of fuzzy interpolative reasoning. It views interpolation procedures as artificially created system components, and identifies all possible sets of faulty components ...
  • Shen, Qiang; Yang, Longzhi (IEEE Press, 2011-09-26)
    Adaptive fuzzy interpolation strengthens the potential of fuzzy interpolative reasoning. It views interpolation procedures as artificially created system components, and identifies all possible sets of faulty components ...
  • Yang, Longzhi; Shen, Qiang (2013-08-16)
    Fuzzy interpolation enhances the robustness of fuzzy systems and helps to reduce systems complexity. Although a number of important fuzzy rule interpolation approaches have been proposed in the literature, most of these ...
  • Yang, Longzhi; Shen, Qiang (2013-08-16)
    Fuzzy interpolation enhances the robustness of fuzzy systems and helps to reduce systems complexity. Although a number of important fuzzy rule interpolation approaches have been proposed in the literature, most of these ...
  • Yang, Longzhi; Chen, Chengyuan; Jin, Nanlin; Fu, Xin; Shen, Qiang (2014)
    Fuzzy rule interpolation enables fuzzy inference with sparse rule bases by interpolating inference results, and may help to reduce system complexity by removing similar (often redundant) neighbouring rules. In particular, ...
  • Yang, Longzhi; Shen, Qiang (2009)
    Fuzzy interpolative reasoning strengthens the power of fuzzy inference by enhancing the robustness of fuzzy systems and reducing systems complexity. However, during the interpolation process, it is possible that multiple ...
  • Shen, Qiang; Yang, Longzhi (2011)
    Fuzzy interpolative reasoning has been extensively studied due to its ability to enhance the robustness of fuzzy systems and reduce system complexity. In particular, the scale and move transformation-based approach is able ...
  • Shen, Qiang; Yang, Longzhi (2011)
    Fuzzy interpolative reasoning has been extensively studied due to its ability to enhance the robustness of fuzzy systems and reduce system complexity. In particular, the scale and move transformation-based approach is able ...
  • Yang, Longzhi; Chao, Fei; Shen, Qiang (2016-07-07)
    As a substantial extension to fuzzy rule interpolation that works based on two neighbouring rules flanking an observation, adaptive fuzzy rule interpolation is able to restore system consistency when contradictory results ...
  • Yang, Longzhi; Shen, Qiang (2009-09-07)
    Fuzzy interpolative reasoning has been extensively studied due to its ability to enhance the robustness of fuzzy systems and to reduce system complexity. However, during the interpolation process, it is possible that ...
  • Yang, Longzhi; Shen, Qiang (2009-08)
    Fuzzy interpolative reasoning has been extensively studied due to its ability to enhance the robustness of fuzzy systems and to reduce system complexity. However, during the interpolation process, it is possible that ...