Comparative Analysis of Symbolic Reasoning Models for Fuzzy Cognitive Maps

Frias, Mabel; Filiberto, Yaima; Nápoles, Gonzalo; Falcón, Rafael; Bello, Rafael; Vanhoof, Koen

doi:10.1007/978-3-030-10463-4_7

Cited by 4 publications

(2 citation statements)

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“…Modeling with words, in Reference 12 , uses linguistic hedge in Reference 13 for implementing process as in Figure 4 with linguistic connection matrix as in Figure 5 and inference based on linguistic tuples with some negative hedges. Our investigation adopt positive in both numeric and linguistic domain for modeling with words in two steps: transform domain and semantic quantify mapping (SQM) in Reference 14 .…”

Section: Reasoning With Wordsmentioning

confidence: 99%

Reasoning with words: A hedge algebra linguistic cognitive map approach

Hán

Vinh

2020

Concurrency and Computation

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In this article, we introduce a method for reasoning with words based on hedge algebra using linguistic cognitive map. Our model consists of set of vertices and edges with value to be linguistic variables which are constrained by linguistic lattice. We figure out relationship between numeric and linguistic domain for fuzzifying data. We also prove convergence theorem on learning method for linguistic cognitive map.

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Section: Reasoning With Wordsmentioning

confidence: 99%

Reasoning with words: A hedge algebra linguistic cognitive map approach

Hán

Vinh

2020

Concurrency and Computation

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“…Fuzzy cognitive maps (FCM) [1]- [6] are fuzzy signed digraphs in which the nodes represent high-level descriptive concepts and the links represent positively or negatively causal influences between concepts, along with the corresponding strengths of these influences.…”

Section: Introductionmentioning

confidence: 99%

Modeling of Complex System Phenomena via Computing With Words in Fuzzy Cognitive Maps

Rickard

Aisbett²,

Morgenthaler

et al. 2020

IEEE Trans. Fuzzy Syst.

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Fuzzy Cognitive Maps (FCMs) play an important role in high level reasoning but are limited in their ability to model complex systems with singularities. We are interested in systems which exhibit discontinuous behaviors as one or more of their internal node states approaches a threshold. In a new approach to FCM dynamics, we define general classes of aggregation functions which "jump" to a boundary value when any input crosses a threshold, or when all inputs do. The threshold value is a contextdependent parameter which can be readily understood by subject matter experts. Aggregation functions are applied separately to positively and negatively causal antecedents to each node then combined to form the nodal state. This modeling is applied in Computing with Words settings, in which link strengths and activation levels are elicited using vocabulary words represented by interval type-2 fuzzy membership functions. We illustrate the behaviors of these novel FCM systems in comparison with their non-singularity versions. Index terms-Aggregation functions, complex systems, computing with words, fuzzy cognitive maps. I.

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