{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T07:01:12Z","timestamp":1777705272153,"version":"3.51.4"},"reference-count":36,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IFS"],"published-print":{"date-parts":[[2021,3,2]]},"abstract":"<jats:p>The article presents a thorough analysis of fuzzy inference introduced by Baldwin and compares this approach to Zaheh\u2019s compositional rule of inference. The comparison is performed in order to analyze the equivalence of the two methods and describe practical aspects of this fact for simple and compound premises, indicating advantages and disadvantages of both approaches. The main aim of the analysis is focus on the computational complexity of the methods. The most important feature of Baldwin\u2019s inference is transfer of the inference process into a truth space, unified for all input variables. Such environment allows to obtain one fuzzy truth value describing a compound premise in a sequence of low dimensional computations. The article proves equality of such approach with the compositional rule of inference. Therefore, this solution is much more computationally efficient in case of compound cases, for which compositional rule of inference is multidimensional.<\/jats:p>","DOI":"10.3233\/jifs-201443","type":"journal-article","created":{"date-parts":[[2021,1,8]],"date-time":"2021-01-08T14:06:43Z","timestamp":1610114803000},"page":"4617-4636","source":"Crossref","is-referenced-by-count":0,"title":["Practical aspects of equivalence of Baldwin\u2019s and Zadeh\u2019s fuzzy inference"],"prefix":"10.1177","volume":"40","author":[{"given":"Przemys\u0142aw","family":"Kud\u0142acik","sequence":"first","affiliation":[{"name":"Institute of Computer Science, University of Silesia, Sosnowiec, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacek M.","family":"\u0141\u0119ski","sequence":"additional","affiliation":[{"name":"Department of Cybernetics, Nanotechnology and Data Processing, Silesian University of Technology, Gliwice, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"key":"10.3233\/JIFS-201443_ref2","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1016\/0165-0114(79)90004-6","article-title":"A new approach to approximate reasoning using a fuzzy logic","volume":"2","author":"Baldwin","year":"1979","journal-title":"Fuzzy Sets and Systems"},{"key":"10.3233\/JIFS-201443_ref3","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/0165-0114(80)90022-6","article-title":"Feasible algorithms for approximate reasoning using fuzzy logic","volume":"2","author":"Baldwin","year":"1980","journal-title":"Fuzzy Sets and Systems"},{"key":"10.3233\/JIFS-201443_ref4","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/0165-0114(80)90054-8","article-title":"Axiomatic approach to implication for approximate reasoning with fuzzy logic","volume":"3","author":"Baldwin","year":"1980","journal-title":"Fuzzy Sets and Systems"},{"key":"10.3233\/JIFS-201443_ref6","doi-asserted-by":"crossref","unstructured":"Bouchon-Meunier B. , Dubois D. , Godo L. and Prade H. , Fuzzy sets in approximate reasoning and information systems. chapter Fuzzy Sets and Possibility Theory in Approximate and Plausible Reasoning. 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