Search results for "Approximate reasoning"

showing 3 items of 3 documents

Integrating resolution—like procedures with Lukasiewicz implication

1993

We discuss some conceptual and technical problems raised by the attempt of integrating resolution-like procedures with the use of Lukukasiewicz implication Min{1, 1 – [a] + [b]} in an environment of approximate reasoning modelled by fuzzy logics.

Deductive reasoningComputer scienceCalculusApproximate reasoningResolution (logic)approximate reasoningFuzzy logicfuzzy logics
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Fuzzy Methods and Approximate Reasoning in Geographical Information Systems

2014

This issue has been dedicated to the usage of fuzzy logic in the context of Geographical Information Systems (GIS) and were receveid the following papers whose contents are described below: - in the paper of A. Hofmann, S. Hoskova-Mayerova, and V. Talhofer, the authors use a GIS tool which is useful to study the influence of geographic and climatic factors on the terrain passability of armed forces and the Integrated Rescue System. - In the first paper of S. Sessa and F. Di Martino, the authors propose the usage of the well known Extended Gustafson-Kessel clustering method, encapsulated in a GIS tool, for detecting hotspots in spatial analysis. The data consist of geo-referenced patterns co…

lcsh:Computer softwareReasoning systemControl and OptimizationFuzzy classificationNeuro-fuzzyArticle SubjectComputer sciencebusiness.industrySPATIAL ANALYSISModel-based reasoningGISFuzzy logicComputational Mathematicslcsh:QA76.75-76.765Control and Systems EngineeringInformation systemFuzzy set operationsApproximate reasoningArtificial intelligencelcsh:Electrical engineering. Electronics. Nuclear engineeringbusinessFUZZY SETSlcsh:TK1-9971Advances in Fuzzy Systems
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Comparison between statistical and fuzzy approaches for improving diagnostic decision making in patients with chronic nasal symptoms

2014

This paper compares a fuzzy model, expressed in rule-form, with a well known statistical approach (i.e. logistic regression model) for diagnostic decision making in patients with chronic nasal symptoms. The analyses were carried out using a database obtained from a questionnaire administered to 1359 patients with nasal symptoms containing personal data, clinical data and skin prick test (SPT) results. Both the fuzzy model and the logistic regression model developed were validated using a data set obtained from another medical institution. The accuracy of the two models in identifying patients with positive or negative SPT was similar. This study is a preliminary step to the creation of a so…

medicine.medical_specialtyLogistic regression modelSettore MED/09 - Medicina InternaSkin prick testLogicFuzzy inference systemFuzzy modelPrimary careSettore MED/10 - Malattie Dell'Apparato RespiratorioFuzzy relationLogistic regressionMachine learningcomputer.software_genreFuzzy logicSettore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Artificial IntelligenceFuzzy modelmedicineIn patientMathematicsNasal symptombusiness.industryApproximate reasoningTest (assessment)Data setPhysical therapyArtificial intelligenceDiagnostic decision makingbusinesscomputerNasal symptomsFuzzy Sets and Systems
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