Fuzzy logic for formal specification of systems

dc.book.titleIADIS International Conference Intelligent Systems and Agents 2008
dc.contributor.authorLópez, Victoria
dc.contributor.authorMontero De Juan, Francisco Javier
dc.date.accessioned2023-06-20T13:41:26Z
dc.date.available2023-06-20T13:41:26Z
dc.date.issued2008
dc.description.abstractNatural languages are daily used to write system specifications. However, language specifications can be confusing and very hard to model and identify. Formal methods for assuring the right behavior of software work very well despite their cost, but it is usually being imposed that specifications are made by means of crisp relations and classical propositional logic. Otherwise, specification can not be properly developed with standard techniques. Since most procedures related to human decisions require fuzzy information, we definitively need to develop alternative approaches allowing fuzziness in order to improve software specification. In this paper we show how fuzzy logic techniques can be used to write specifications in a fuzzy framework, as a previous step in the process of analysis and design of new software. As an example, we consider a multiprocessor system, showing how to make a formal specification of the system focused in a particular goal: to improve the performance of the system. We briefly introduce the classical formal specification by means of formal methods, and then we show more in detail the same specification by means of fuzzy techniques (fuzzy sets and granules as new generic types of data). Several possibilities for formal specification are presented. In this way, we will show how an information closer to the natural language can be managed in terms of fuzzy sets and fuzzy inference rules.en
dc.description.departmentDepto. de Estadística e Investigación Operativa
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedTRUE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/29005
dc.identifier.isbn978-972-8924-60-7
dc.identifier.urihttps://hdl.handle.net/20.500.14352/53397
dc.language.isoeng
dc.page.final218
dc.page.initial215
dc.publisherISA
dc.rights.accessRightsrestricted access
dc.subject.cdu004.8
dc.subject.keywordFuzzy logic
dc.subject.keywordFormal specification
dc.subject.keywordFormal languages.
dc.subject.ucmInteligencia artificial (Informática)
dc.subject.unesco1203.04 Inteligencia Artificial
dc.titleFuzzy logic for formal specification of systemsen
dc.typebook part
dcterms.referencesBellman, R. A. and Zadeh, L.A., 1970. Decision-making in a fuzzy environment. Management Sciences, Ser. B. 17 pp.141-164. López, V. and Montero, J., 2007. Fuzzy specification in software engineering, Proceedings of the Joint Conference on Infomation Sciences, World Scientific, Salt Lake City, USA. López, V., Garmendia, L., Montero, J., and Resconi, G.,2008. Specification and computing states in fuzzy algorithms. International Journal for Uncertainty, Fuzziness and Knowledge-based Systems (In press). Montero, J., Gómez, D. and Bustince, H. 2007. On the relevance of some families of fuzzy sets.. Fuzzy Sets and Systems 158: 2429-2442. Montero, J., López, V., and Gómez, D., 2007. The role of fuzziness in decision making. In D. Ruan et al. , Eds.,Fuzzy Logic: an spectrum of applied and theoretical issues,Springer, pp. 337-349. Pedrycz, W., Skowron, A. and Kreinovich , V. (Eds.), 2008: Handbook of Granular Computing, Willey. Spivey, J. M., 1998. The Z notation: A reference manual, Prentice-Hall. Woodcock, J., and Davis, J., 1997. Using Z: Specification, refinement and proof, Prentice Hall. Zadeh, L.A., 2001. From computing with numbers to computing with words-From manipulation of measurements to manipulation of perceptions. In P.P. Wang, Ed., Computing with words, Willey, pp. 35-68.
dspace.entity.typePublication
relation.isAuthorOfPublication9e4cf7df-686c-452d-a98e-7b2602e9e0ea
relation.isAuthorOfPublication.latestForDiscovery9e4cf7df-686c-452d-a98e-7b2602e9e0ea

Download

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Montero117.pdf
Size:
327.04 KB
Format:
Adobe Portable Document Format