Control system
A control system is a device, or set of devices, that manages, commands, directs or regulates the behavior of other devices or systems. Industrial control systems are used in industrial production for...
Bang-bang control
In control theory, a bang–bang controller (on–off controller), also known as a hysteresis controller, is a feedback controller that switches abruptly between two states. These controllers may be reali...
Fuzzy logic
Fuzzy logic is a form of many-valued logic that deals with approximate, rather than fixed and exact reasoning. Compared to traditional binary logic (where variables may take on true or false values), ...
Fuzzy Pay-Off Method for Real Option Valuation
The fuzzy pay-off method for real option valuation (FPOM or pay-off method) is a new method for valuing real options, created in 2008. It is based on the use of fuzzy logic and fuzzy numbers for the ...
Fuzzy set operations
A fuzzy set operation is an operation on fuzzy sets. These operations are generalization of crisp set operations. There is more than one possible generalization. The most widely used operations are ...
Bate's chip
Bates's chip (also called a sloppy chip or fuzzy chip) is a theoretical chip proposed by MIT Media Lab's computer scientist Joseph Bates that would incorporate fuzzy logic to do calculations. The resu...
BL (logic)
Basic fuzzy Logic (or shortly BL), the logic of continuous t-norms, is one of t-norm fuzzy logics. It belongs to the broader class of substructural logics, or logics of residuated lattices; it extends...
Type-1 OWA operators
The Yager's OWA (ordered weighted averaging) operators have been widely used to aggregate the crisp values in decision making schemes (such as multi-criteria decision making, multi-expert decisin mak...
Ordered Weighted Averaging (OWA) Aggregation Operators
In applied mathematics – specifically in fuzzy logic – the ordered weighted averaging (OWA) operators provide a parameterized class of mean type aggregation operators. They were introduced by Ronald R...
Fuzzy finite element
The fuzzy finite element method combines the well-established finite element method with the concept of fuzzy numbers, the latter being a special case of a fuzzy set. The advantage of using fuzzy numb...
Fuzzy rule
A fuzzy rule is defined as a conditional statement in the form:where x and y are linguistic variables; A and B are linguistic values determined by fuzzy sets on the universe of discourse X and Y, resp...
Monoidal t-norm logic
Monoidal t-norm based logic (or shortly MTL), the logic of left-continuous t-norms, is one of t-norm fuzzy logics. It belongs to the broader class of substructural logics, or logics of residuated latt...
Possibility theory
Possibility theory is a mathematical theory for dealing with certain types of uncertainty and is an alternative to probability theory. Professor Lotfi Zadeh first introduced possibility theory in 1978...
T-norm
In mathematics, a t-norm (also T-norm or, unabbreviated, triangular norm) is a kind of binary operation used in the framework of probabilistic metric spaces and in multi-valued logic, specifically in ...
T-norm fuzzy logics
T-norm fuzzy logics are a family of non-classical logics, informally delimited by having a semantics which takes the real unit interval [0, 1] for the system of truth values and functions called ...
Perceptual Computing
Perceptual computing is an application of Zadeh's theory of computing with words on the field of assisting people to make subjective judgments.
The perceptual computer – Per-C – an instantiation o...
Fuzzy Sets and Systems
Fuzzy Sets and Systems is a peer-reviewed international scientific journal published by Elsevier on behalf of the International Fuzzy Systems Association (IFSA) and was founded in 1978. The editors-in...
Predicate (mathematical logic)
In mathematics, a predicate is commonly understood to be a Boolean-valued function P: X→ {true, false}, called the predicate on X. However, predicates have many different uses and interpretations in m...
Adaptive Neuro Fuzzy Inference System
An adaptive neuro-fuzzy inference system or adaptive network-based fuzzy inference system (ANFIS) is a kind of artificial neural network that is based on Takagi–Sugeno fuzzy inference system. The tech...
Residuated Boolean algebra
In mathematics, a residuated Boolean algebra is a residuated lattice whose lattice structure is that of a Boolean algebra. Examples include Boolean algebras with the monoid taken to be conjunction, th...
Linear partial information
Linear partial information (LPI) is a method of making decisions based on insufficient or fuzzy information. LPI was introduced in 1970 by Polish - Swiss mathematician Edward Kofler (1911–2007) to sim...
Fuzzy routing
Fuzzy routing is the application of fuzzy logic to routing protocols, particularly in the context of ad-hoc wireless networks and in networks supporting multiple quality of service classes. It is curr...
High Performance Fuzzy Computing
The term High Performance Fuzzy Computing (HPFC) refers tothose technologies able to exploit supercomputers and computer clustersto perform high performance Fuzzy Logic computations.Thus HPFC is just ...
Construction of t-norms
In mathematics, t-norms are a special kind of binary operations on the real unit interval [0, 1]. Various constructions of t-norms, either by explicit definition or by transformation from previou...
Degree of truth
In standard mathematics, propositions can typically be considered unambiguously true or false. For instance, the proposition zero belongs to the set { 1 } is regarded as simply false; while the propos...
Fuzzy cognitive map
A Fuzzy cognitive map is a cognitive map within which the relations between the elements (e.g. concepts, events, project resources) of a "mental landscape" can be used to compute the "strength of impa...
Fuzzy measure theory
In mathematics, fuzzy measure theory considers generalized measures in which the additive property is replaced by the weaker property of monotonicity. The central concept of fuzzy measure theory is t...
Fuzzy number
A fuzzy number is an generalization of a regular, real number in the sense that it does not refer to one single value but rather to a connected set of possible values, where each possible value has it...
Membership function (mathematics)
The membership function of a fuzzy set is a generalization of the indicator function in classical sets. In fuzzy logic, it represents the degree of truth as an extension of valuation. Degrees of trut...