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001			978-981-97-0491-0
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005			20240423130339.0
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008			240408s2024 si | s |||| 0|eng d
020			_a9789819704910 _9978-981-97-0491-0
024	7		_a10.1007/978-981-97-0491-0 _2doi
050		4	_aQ334-342
050		4	_aTA347.A78
072		7	_aUYQ _2bicssc
072		7	_aCOM004000 _2bisacsh
072		7	_aUYQ _2thema
082	0	4	_a006.3 _223
100	1		_aLi, Fangyi. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aFuzzy Rule-Based Inference _h[electronic resource] : _bAdvances and Applications in Reasoning with Approximate Knowledge Interpolation / _cby Fangyi Li, Qiang Shen.
250			_a1st ed. 2024.
264		1	_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2024.
300			_aXIV, 187 p. 44 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_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.
520			_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.
650		0	_aArtificial intelligence.
650		0	_aExpert systems (Computer science).
650		0	_aComputers, Special purpose.
650		0	_aPattern recognition systems.
650		0	_aApplication software.
650		0	_aImage processing _xDigital techniques.
650		0	_aComputer vision.
650	1	4	_aArtificial Intelligence.
650	2	4	_aKnowledge Based Systems.
650	2	4	_aSpecial Purpose and Application-Based Systems.
650	2	4	_aAutomated Pattern Recognition.
650	2	4	_aComputer and Information Systems Applications.
650	2	4	_aComputer Imaging, Vision, Pattern Recognition and Graphics.
700	1		_aShen, Qiang. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9789819704903
776	0	8	_iPrinted edition: _z9789819704927
776	0	8	_iPrinted edition: _z9789819704934
856	4	0	_uhttps://doi.org/10.1007/978-981-97-0491-0
912			_aZDB-2-SCS
912			_aZDB-2-SXCS
942			_cSPRINGER
999			_c187613 _d187613