Abstract
A fuzzy rules extraction based-integration (FREI) method is proposed to integrate numerical data from measuring instruments and linguistic rules from human experts. At first, the fuzzy IF-THEN rules are extracted from numerical data and acquired from experts individually. Based on a simple and intuitive integration scheme, a uniform fuzzy rules base is constructed through integrating above two kinds of information. The integrated information can be used for hybrid intelligent systems (HIS) design. With inverse learning, the proposed FREI method is able to integrate linguistic and numerical information with various forms, such as direct and indirect, and thus improve the performance of HIS using a priori knowledge where it is available. The validity of the proposed methods are verified through the fuzzy rules extraction-based hybrid intelligent control of a biped walking robot.
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Zhou, C., Meng, Q. (1998). Fuzzy rules extraction based-integration of linguistic and numerical information for hybrid intelligent systems. In: Lee, HY., Motoda, H. (eds) PRICAI’98: Topics in Artificial Intelligence. PRICAI 1998. Lecture Notes in Computer Science, vol 1531. Springer, Berlin, Heidelberg . https://doi.org/10.1007/BFb0095277
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DOI: https://doi.org/10.1007/BFb0095277
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