LEADER 05165nam 22007215 450 001 9910847579503321 005 20250807145701.0 010 $a981-9704-91-X 024 7 $a10.1007/978-981-97-0491-0 035 $a(CKB)31403590700041 035 $a(MiAaPQ)EBC31261000 035 $a(Au-PeEL)EBL31261000 035 $a(DE-He213)978-981-97-0491-0 035 $a(EXLCZ)9931403590700041 100 $a20240408d2024 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aFuzzy Rule-Based Inference $eAdvances and Applications in Reasoning with Approximate Knowledge Interpolation /$fby Fangyi Li, Qiang Shen 205 $a1st ed. 2024. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2024. 215 $a1 online resource (195 pages) 311 08$a981-9704-90-1 327 $a1 Introduction -- 2 Framework of Fuzzy Rule Interpolation -- 3 Attribute Weighting and Weighted Fuzzy Rule Bases -- 4 Attribute Weighted Fuzzy Rule-based Inference -- 5 Attribute Weighted Fuzzy Interpolative Reasoning -- 6 Practical Integrated Weighted Approximate Reasoning -- 7 Practical Application to Interpretable Medical Risk Analysis -- 8 Conclusion. 330 $aThis book covers a comprehensive approach to the development and application of a suite of novel algorithms for practical approximate knowledge-based inference. It includes an introduction to the fundamental concepts of fuzzy sets, fuzzy logic, and fuzzy inference. Collectively, this book provides a systematic tutorial and self-contained reference to recent advances in the field of fuzzy rule-based inference. Approximate reasoning systems facilitate inference by utilizing fuzzy if-then production rules for decision-making under circumstances where knowledge is imprecisely characterized. Compositional rule of inference (CRI) and fuzzy rule interpolation (FRI) are two typical techniques used to implement such systems. The question of when to apply these potentially powerful reasoning techniques via automated computation procedures is often addressed by checking whether certain rules can match given observations. Both techniques have been widely investigated to enhance the performance of approximate reasoning. Increasingly more attention has been paid to the development of systems where rule antecedent attributes are associated with measures of their relative significance or weights. However, they are mostly implemented in isolation within their respective areas, making it difficult to achieve accurate reasoning when both techniques are required simultaneously. This book first addresses the issue of assigning equal significance to all antecedent attributes in the rules when deriving the consequents. It presents a suite of weighted algorithms for both CRI and FRI fuzzy inference mechanisms. This includes an innovative reverse engineering process that can derive attribute weightings from given rules, increasing the automation level of the resulting systems. An integrated fuzzy reasoning approach is then developed from these two sets of weighted improvements, showcasing more effective and efficient techniques for approximate reasoning. Additionally, the book provides an overarching application to interpretable medical risk analysis, thanks to the semantics-rich fuzzy rules with attribute values represented in linguistic terms. Moreover, it illustrates successful solutions to benchmark problems in the relevant literature, demonstrating the practicality of the systematic approach to weighted approximate reasoning. 606 $aArtificial intelligence 606 $aExpert systems (Computer science) 606 $aComputers, Special purpose 606 $aPattern recognition systems 606 $aApplication software 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aArtificial Intelligence 606 $aKnowledge Based Systems 606 $aSpecial Purpose and Application-Based Systems 606 $aAutomated Pattern Recognition 606 $aComputer and Information Systems Applications 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 615 0$aArtificial intelligence. 615 0$aExpert systems (Computer science) 615 0$aComputers, Special purpose. 615 0$aPattern recognition systems. 615 0$aApplication software. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 14$aArtificial Intelligence. 615 24$aKnowledge Based Systems. 615 24$aSpecial Purpose and Application-Based Systems. 615 24$aAutomated Pattern Recognition. 615 24$aComputer and Information Systems Applications. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 676 $a910.5 700 $aLi$b Fangyi$01736263 702 $aShen$b Qiang 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910847579503321 996 $aFuzzy Rule-Based Inference$94270356 997 $aUNINA