Free Quantification in Four-Valued and Fuzzy Bilattice-Valued Logics

We introduce a variant of free logic (i.e., a logic admitting terms with nonexistent referents) that accommodates truth-value gluts as well as gaps. Employing a suitable expansion of the Belnap--Dunn four-valued logic, we specify a dual-domain semantics for free logic, in which propositions containing non-denoting terms can be true, false, neither true nor false, or both true and false. In each model, the dual domain semantics separates existing and non-existing objects into two subdomains, making it possible to quantify either over all objects or existing objects only. We also outline a fuzzy variant of the dual-domain semantics, accommodating non-denoting terms in fuzzy contexts that can be partially indeterminate or inconsistent.Comment: 12 pages, submitted to IUKM 2023 Conferenc

Some Epistemic Extensions of G\"odel Fuzzy Logic

In this paper, we introduce some epistemic extensions of G\"odel fuzzy logic whose Kripke-based semantics have fuzzy values for both propositions and accessibility relations such that soundness and completeness hold. We adopt belief as our epistemic operator, then survey some fuzzy implications to justify our semantics for belief is appropriate. We give a fuzzy version of traditional muddy children problem and apply it to show that axioms of positive and negative introspections and Truth are not necessarily valid in our basic epistemic fuzzy models. In the sequel, we propose a derivation system $K_F$ as a fuzzy version of classical epistemic logic $K$. Next, we establish some other epistemic-fuzzy derivation systems $B_F, T_F, B_F^n$ and $T_F^n$ which are extensions of $K_F$, and prove that all of these derivation systems are sound and complete with respect to appropriate classes of Kripke-based models

Blended intelligence of FCA with FLC for knowledge representation from clustered data in medical analysis

Formal concept analysis is the process of data analysis mechanism with emergent attractiveness across various fields such as data mining, robotics, medical, big data and so on. FCA is helpful to generate the new learning ontology based techniques. In medical field, some growing kids are facing the problem of representing their knowledge from their gathered prior data which is in the form of unordered and insufficient clustered data which is not supporting them to take the right decision on right time for solving the uncertainty based questionnaires. In the approach of decision theory, many mathematical replicas such as probability-allocation, crisp set, and fuzzy based set theory were designed to deals with knowledge representation based difficulties along with their characteristic. This paper is proposing new ideological blended approach of FCA with FLC and described with major objectives: primarily the FCA analyzes the data based on relationships between the set of objects of prior-attributes and the set of attributes based prior-data, which the data is framed with data-units implicated composition which are formal statements of idea of human thinking with conversion of significant intelligible explanation. Suitable rules are generated to explore the relationship among the attributes and used the formal concept analysis from these suitable rules to explore better knowledge and most important factors affecting the decision making. Secondly how the FLC derive the fuzzification, rule-construction and defuzzification methods implicated for representing the accurate knowledge for uncertainty based questionnaires. Here the FCA is projected to expand the FCA based conception with help of the objective based item set notions considered as the target which is implicated with the expanded cardinalities along with its weights which is associated through the fuzzy based inference decision rules. This approach is more helpful for medical experts for knowing the range of patient’s memory deficiency also for people whose are facing knowledge explorer deficiency

Multivalued logic systems for technical applications

Velmi často je vyžadováno, aby automatizovaná zařízení byla jistým způsobem "inteligentní", tedy aby jejich řídicí systémy uměly emulovat rozhodovací proces. Tato diplomová práce poskytuje obecný formální popis vícehodnotových logických systémů schopných zmíněné emulace a jejich souvislost s teorií fuzzy množin. Jsou uvedeny způsoby vytváření matematických modelů založených na lingvistických datech. Dále se práce zabývá znalostními bázemi a jejich vlastnostmi. Součástí této práce je také počítačový program sloužící k tvorbě slovních modelů.Automated devices are very often required to exhibit some kind of an intelligent behaviour, which means that their control systems must be able to emulate the reasoning process. This diploma thesis provides a general formal description of multivalued logic systems capable of such an emulation and their connection with the fuzzy set theory. Ways of constructing mathematical models based on linguistic data are described. Also, knowledge bases and their properties are discussed. A computer program serving as a linguistic model development tool is a part of this thesis.

The legacy of 50 years of fuzzy sets: A discussion

International audienceThis note provides a brief overview of the main ideas and notions underlying fifty years of research in fuzzy set and possibility theory, two important settings introduced by L.A. Zadeh for representing sets with unsharp boundaries and uncertainty induced by granules of information expressed with words. The discussion is organized on the basis of three potential understanding of the grades of membership to a fuzzy set, depending on what the fuzzy set intends to represent: a group of elements with borderline members, a plausibility distribution, or a preference profile. It also questions the motivations for some existing generalized fuzzy sets. This note clearly reflects the shared personal views of its authors

Diagnosis Blood Test for Liver Disease using Fuzzy Logic

Most commonly lab test used to measure or monitor general health and liver health are following: Liver Biochemical/Function test, CBC and Chemistry Panel. In this thesis we are focusing on CBC. Complete Blood Counts measure the four components of blood leukocytes, Hematocrit, Hemoglobin and Blood Platelets. For this purpose we design fuzzy control model which help to diagnose a disease related to human liver. Fuzzy design model have four input variables (leukocytes, hematocrit, hemoglobin, blood platelets) and three output variables (infection fight, anemia and thrombocytopenia). Fuzzy design model algorithm divided into four steps Fuzzification, Inference Engine, Rule selector and Defuzzification. Each input variable and output variable graphically represented by M

An Holistic Extension for Classical Logic via Quantum Fredkin Gate

An holistic extension for classical propositional logic is introduced in the framework of quantum computation with mixed states. The mentioned extension is obtained by applying the quantum Fredkin gate to non-factorizable bipartite states. In particular, an extended notion of classical contradiction is studied in this holistic framework