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dc.contributor.author Qiang en_US
dc.contributor.author Yang en_US
dc.date.accessioned 2011-06-08T14:11:40Z
dc.date.available 2011-06-08T14:11:40Z
dc.date.issued 2011 en_US
dc.identifier.citation Shen , Q & Longzhi , Y 2011 , ' Generalisation of Scale and Move Transformation-Based Fuzzy Interpolation ' Journal of Advanced Computational Intelligence and Intelligent Informatics , vol 15 , no. 3 , pp. 288-298 . en_US
dc.identifier.other PURE: 160719 en_US
dc.identifier.other dspace: 2160/7009 en_US
dc.identifier.uri http://hdl.handle.net/2160/7009
dc.description.abstract 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 to handle interpolation with multiple antecedent rules involving triangular, complex polygon, Gaussian and bell-shaped fuzzy membership functions [1]. Also, this approach has been extended to deal with interpolation and extrapolation with multiple multi-antecedent rules [2]. However, the generalised extrapolation approach based on multiple rules may not degenerate back to the basic crisp extrapolation based on two rules. Besides, the approximate function of the extended approach may not be continuous. This paper therefore proposes a new approach to generalising the basic fuzzy interpolation technique of [1] in an effort to eliminate these limitations. Examples are given throughout the paper for illustration and comparative purposes. The result shows that the proposed approach avoids the identified problems, providing more reasonable interpolation and extrapolation. en_US
dc.format.extent 11 en_US
dc.relation.ispartof Journal of Advanced Computational Intelligence and Intelligent Informatics en_US
dc.title Generalisation of Scale and Move Transformation-Based Fuzzy Interpolation en_US
dc.contributor.pbl Department of Computer Science en_US
dc.contributor.pbl Advanced Reasoning Group en_US


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