Interpretability constraints for fuzzy information granulation

Mencar, Corrado; Fanelli, Anna Maria

doi:10.1016/j.ins.2008.08.015

Cited by 157 publications

(122 citation statements)

References 133 publications

(195 reference statements)

Supporting

Mentioning

109

Contrasting

Unclassified

Order By: Relevance

“…The implementation was developed with the "Fuzzy" toolbox (v. To represent the semantic of the interior (extreme) labels of all domains, triangular (trapezoidal) fuzzy numbers (TFNs) were considered, since many authors consider them robust enough to linguistically express the ambiguous valuations given by the sources of information [85]. Regarding the design, strong fuzzy partitions were chosen [86], as they prove to be optimal in terms of comprehensibility by satisfying important semantics constraints as distinguishability, normalization, coverage or overlapping [87].…”

Section: Fuzzy Inference System (Fis)mentioning

confidence: 99%

“…(iii) Preference assessment {Si} from the experts for each proposed structure (see Table 6). (iv) In each structure, aggregate all the expert estimations (e.g., through the "Extended Arithmetic Mean (EAM)", taking as values the order of labels in the scale {Si} [87]. Example: EAM (Struc_1) = (0 × 0 + 1 × 2 + 2 × 2)/4 = 1.5).…”

Section: Fuzzy Inference System (Fis)mentioning

confidence: 99%

See 1 more Smart Citation

Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

et al. 2018

View full text Add to dashboard Cite

This paper designs a bidding and supplier evaluation model focused on strategic product procurement, and develops their respective evaluation knowledge bases. The model is built using the most relevant variables cited in the reviewed procurement literature and allows to compare two evaluation methods: a factor weighting method (WM) and a fuzzy inference system (FIS). By consulting an expert panel and using a two-tuples symbolic translation system, strong fuzzy partitions for all model variables are built. The method, based on central symmetry, permits to obtain the fuzzy label borders from their cores, which have been previously agreed among experts. The system also allows to agree the fuzzy rules to embed in the FIS. The results show the FIS method's superiority as it allows to better manage the non-linear behavior and the uncertainty inherent to the supplier evaluation process.

show abstract

Section: Fuzzy Inference System (Fis)mentioning

confidence: 99%

Section: Fuzzy Inference System (Fis)mentioning

confidence: 99%

Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

et al. 2018

View full text Add to dashboard Cite

show abstract

“…More specifically, while designing an interpretable fuzzy model the data domain is represented through linguistic variables (usually one for each data feature); given a linguistic variable, the fuzzy sets associated to each linguistic term form a fuzzy partition of the data feature. To ensure interpretability, a number of constraints are imposed on the fuzzy sets of each fuzzy partition, like distinguishability, coverage, special elements, and so on [1].…”

Section: Introductionmentioning

confidence: 99%

“…Cuts can be conveniently used to define the bounds of the 0.5-cuts of the fuzzy sets in a fuzzy partition 1 . More specifically, given a collection of cuts, a SFP can be defined so that the 0.5-cuts of the fuzzy sets in the partition coincide with the intervals bounded by the cuts (see fig.…”

Section: Introductionmentioning

confidence: 99%

Design of Strong Fuzzy Partitions from Cuts

Mencar¹,

Lucarelli²,

Castiello³

et al. 2013

Proceedings of the 8th Conference of the European Society for Fuzzy Logic and Technology

View full text Add to dashboard Cite

The adoption of triangular fuzzy sets to define Strong Fuzzy Partitions (SFPs) is a common practice in the research community: due to their inherent simplicity, triangular fuzzy sets can be easily derived from data by applying suitable clustering algorithms. However, the choice of triangular fuzzy sets may be limiting for the modeling process. In this paper we focus on SFPs built up starting from cuts (points of separation between cluster projections on data dimensions), showing that a SFP based on cuts can always be defined by trapezoidal fuzzy sets. Different mechanisms to derive SFPs from cuts are presented and compared by employing DC*, an algorithm for extracting fuzzy information granules from classified data.

show abstract

“…Considering the interpretability and due to its subjective nature and the large amount of factors involved, the choice of appropriate measures is still an open problem 21,28,[30][31][32][33][34] . In the specialist literature, there are proposal of different measures 27,28,[30][31][32][33][34] and techniques [8][9][10]22,23,[35][36][37] for obtaining more interpretable linguistic fuzzy models.…”

Section: Introductionmentioning

confidence: 99%

A Mechanism to Improve the Interpretability of Linguistic Fuzzy Systems with Adaptive Defuzzification based on the use of a Multi-objective Evolutionary Algorithm

Márquez¹,

Márquez²,

Peregrín³

2012

IJCIS

View full text Add to dashboard Cite

This paper proposes a mechanism that helps improve the interpretability of linguistic fuzzy ruled based systems with common adaptive defuzzification methods. Adaptive defuzzification significantly improves the system accuracy, but introduces weights associated with each rule of the rule base, decreasing the system interpretability. The suggested mechanism is based on three goals: 1) reducing the number of total rules considering that rule weight close to zero can be removed; 2) reducing the rules with weights coupled because rules with weights close to one do not need the weight, and 3) reducing rules triggered jointly, all of them by using several metrics and a proposed interpretability index. This is performed using a multi-objective evolutionary algorithm, obtaining a set of solutions with different trade-offs between accuracy and interpretability. In addition, it is important to note that adaptive defuzzification and therefore the proposal developed in this work can be used together with other methodologies to improve system interpretability and accuracy, so it can be viewed as an interesting component.

show abstract

Interpretability constraints for fuzzy information granulation

Cited by 157 publications

References 133 publications

Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

Suitability of a Consensual Fuzzy Inference System to Evaluate Suppliers of Strategic Products

Design of Strong Fuzzy Partitions from Cuts

A Mechanism to Improve the Interpretability of Linguistic Fuzzy Systems with Adaptive Defuzzification based on the use of a Multi-objective Evolutionary Algorithm

Contact Info

Product

Resources

About