9,830 research outputs found
A New Penta-valued Logic Based Knowledge Representation
In this paper a knowledge representation model are proposed, FP5, which
combine the ideas from fuzzy sets and penta-valued logic. FP5 represents
imprecise properties whose accomplished degree is undefined, contradictory or
indeterminate for some objects. Basic operations of conjunction, disjunction
and negation are introduced. Relations to other representation models like
fuzzy sets, intuitionistic, paraconsistent and bipolar fuzzy sets are
discussed.Comment: The 12th International Conference Information Processing and
Management of Uncertainty in Knowledge-Based Systems, June 22-27, 2008,
Malaga, Spai
Approximate Reasoning with Fuzzy Booleans
This paper introduces, in analogy to the concept of fuzzy numbers, the concept of fuzzy booleans, and examines approximate reasoning with the compositional rule of inference using fuzzy booleans. It is shown that each set of fuzzy rules is equivalent to a set of fuzzy rules with singleton crisp antecedents; in case of fuzzy booleans this set contains only two rules. It is shown that Zadeh's extension principle is equivalent to the compositional rule of inference using a complete set of fuzzy rules with singleton crisp antecedents. The results are applied to describe the use of approximate reasoning with fuzzy booleans to object-oriented design methods
n-Valued Refined Neutrosophic Logic and Its Applications to Physics
In this paper we present a short history of logics: from particular cases of
2-symbol or numerical valued logic to the general case of n-symbol or numerical
valued logic. We show generalizations of 2-valued Boolean logic to fuzzy logic,
also from the Kleene and Lukasiewicz 3-symbol valued logics or Belnap 4-symbol
valued logic to the most general n-symbol or numerical valued refined
neutrosophic logic. Two classes of neutrosophic norm (n-norm) and neutrosophic
conorm (n-conorm) are defined. Examples of applications of neutrosophic logic
to physics are listed in the last section. Similar generalizations can be done
for n-Valued Refined Neutrosophic Set, and respectively n- Valued Refined
Neutrosopjhic Probability.Comment: 9 page
Conceptual design and implementation of the fuzzy semantic model
FSM is one of few database models that support
fuzziness, uncertainty and impreciseness of real-world at the class
definition level. FSM authorizes an entity to be partially member
of its class according to a given degree of membership that reflects
the level to which the entity verifies the extent properties of this
class. This paper deals with the conceptual design of FSM and
adresses some implementation issues.ou
Constraint-wish and satisfied-dissatisfied: an overview of two approaches for dealing with bipolar querying
In recent years, there has been an increasing interest in dealing with user preferences in flexible database querying, expressing both positive and negative information in a heterogeneous way. This is what is usually referred to as bipolar database querying. Different frameworks have been introduced to deal with such bipolarity. In this chapter, an overview of two approaches is given. The first approach is based on mandatory and desired requirements. Hereby the complement of a mandatory requirement can be considered as a specification of what is not desired at all. So, mandatory requirements indirectly contribute to negative information (expressing what the user does not want to retrieve), whereas desired requirements can be seen as positive information (expressing what the user prefers to retrieve). The second approach is directly based on positive requirements (expressing what the user wants to retrieve), and negative requirements (expressing what the user does not want to retrieve). Both approaches use pairs of satisfaction degrees as the underlying framework but have different semantics, and thus also different operators for criteria evaluation, ranking, aggregation, etc
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