Uncertainty Handling with Type-2 Interval-Valued Fuzzy Logic in IoT Resource Classification

Dilli, Renato; Reiser, Renata; Yamin, Adenauer; Santos, Hélida; Lucca, Giancarlo

doi:10.1007/978-3-031-28451-9_8

Cited by 1 publication

(2 citation statements)

References 14 publications

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“…In order to overcome this structure, interval-valued fuzzy logic has been suggested. This interval logic is a particular case of interval type-2 fuzzy logic [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

“…Interval-valued fuzzy logic has been applied in a wide variety of domains; for example, Melin and Castillo [7] used it in the context of plant control; Figueroa et al [8] used it for non-autonomous robots in the context of a robot football game; Lynch et al [9] built an interval control system for large marine diesel engines; Chourasia et al [10] developed a new method for assessing fetal health status based on interval type-2 fuzzy logic through fetal phonocardiography; Nguyen et al [11] used the wavelet feature in an interval type-2 fuzzy logic system (IT2FLS) to reduce the computation burden and time of IT2FLS; Leow et al [12] developed a hybrid of generalized adaptive resonance theory (GART) and an interval type-2 fuzzy logic system algorithm; among many others [5,6].…”

Section: Introductionmentioning

confidence: 99%

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Developing Constrained Interval Operators for Fuzzy Logic with Interval Values

Pinheiro,

Santiago,

Bedregal

et al. 2023

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A well-known problem in the interval analysis literature is the overestimation and loss of information. In this article, we define new interval operators, called constrained interval operators, that preserve information and mitigate overestimation. These operators are investigated in terms of correction, algebraic properties, and orders. It is shown that a large part of the properties studied is preserved by this operator, while others remain preserved with the condition of continuity, as is the case of the exchange principle. In addition, a comparative study is carried out between this operator g¨ and the best interval representation: g^. Although g¨⊆g^ and g¨ do not preserve the Moore correction, we do not have a loss of relevant information since everything that is lost is irrelevant, mitigating the overestimation.

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“…In order to overcome this structure, interval-valued fuzzy logic has been suggested. This interval logic is a particular case of interval type-2 fuzzy logic [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%