Application of OWA Operators in the L-Fuzzy Concept Analysis

2013 ◽  
pp. 129-140 ◽  
Author(s):  
C. Alcalde ◽  
A. Burusco ◽  
R. Fuentes-González
Keyword(s):  
Concept Analysis ◽  
Owa Operators ◽  
Fuzzy Concept

L-Fuzzy Concept Analysis as a Decision-Making Tool in the Development of Bio-Based Materials

2020 ◽  
Author(s):  
Itsaso Leceta ◽  
Cristina Alcalde ◽  
Marta Urdanpilleta ◽  
Pedro Guerrero ◽  
Koro de la Caba ◽  
...  
Keyword(s):  
Wound Healing ◽  
Food Packaging ◽  
Cost Effective ◽  
Concept Analysis ◽  
Water Contact ◽  
Elongation At Break ◽  
Fuzzy Concept ◽  
Fatty Food ◽  
Decision Making Tool

Abstract The use of L-fuzzy concept analysis for the determination of the formulations of gelatin-based films that fulfillspecifc functional properties is reported. The requirements of water contact angle (CA), water vapourtransmission rate (WVTR), L* and b* colour values, tensile strength (TS), elongation at break (EB) and glossvalues were specified for both fatty food packaging and wound healing applications. Once the requiredformulations were estimated by L-fuzzy concepts, the experimental results showed a high accordance with thepredicted values of the nal properties, as well as with the requirements. The errors were lower than 20% in allcases, except in colour (for food packaging) and gloss and elongation at break (for wound healing), in whichthe nal properties were even better that the estimations. This analysis allowed nding the requiredformulations in a highly cost-effective way.

scholarly journals Block relations in formal fuzzy concept analysis

2016 ◽  
Vol 73 ◽  
pp. 27-55 ◽  
Author(s):  
Jan Konecny ◽  
Michal Krupka
Keyword(s):  
Concept Analysis ◽  
Fuzzy Concept ◽  
Formal Fuzzy Concept

Making sense of cloud-sensor data streams via Fuzzy Cognitive Maps and Temporal Fuzzy Concept Analysis

2017 ◽  
Vol 256 ◽  
pp. 35-48 ◽  
Author(s):  
Carmen De Maio ◽  
Giuseppe Fenza ◽  
Vincenzo Loia ◽  
Francesco Orciuoli
Keyword(s):  
Data Streams ◽  
Cognitive Maps ◽  
Concept Analysis ◽  
Fuzzy Cognitive Maps ◽  
Sensor Data ◽  
Fuzzy Concept ◽  
Making Sense

Some Relationships Between Fuzzy Sets, Mathematical Morphology, Rough Sets, F-Transforms, and Formal Concept Analysis

2016 ◽  
Vol 24 (Suppl. 2) ◽  
pp. 1-32 ◽  
Author(s):  
Jamal Atif ◽  
Isabelle Bloch ◽  
Céline Hudelot
Keyword(s):  
Fuzzy Sets ◽  
Mathematical Morphology ◽  
Rough Sets ◽  
Formal Concept Analysis ◽  
Concept Lattice ◽  
Concept Analysis ◽  
Formal Concept ◽  
Fuzzy Concept Lattice ◽  
Fuzzy Concept ◽  
Potential Interest

In this paper we extend some previously established links between the derivation operators used in formal concept analysis and some mathematical morphology operators to fuzzy concept analysis. We also propose to use mathematical morphology to navigate in a fuzzy concept lattice and perform operations on it. Links with other lattice-based for malisms such as rough sets and F-transforms are also established. This paper proposes a discussion and new results on such links and their potential interest.

scholarly journals Representation of Fuzzy Concept Lattices in the Framework of Classical FCA

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Peter Butka ◽  
Jozef Pócs ◽  
Jana Pócsová
Keyword(s):  
Formal Concept Analysis ◽  
Concept Lattice ◽  
Concept Analysis ◽  
Formal Concept ◽  
Concept Lattices ◽  
Fuzzy Concept Lattice ◽  
Galois Connections ◽  
Fuzzy Concept ◽  
Needed Information

We describe a representation of the fuzzy concept lattices, defined via antitone Galois connections, within the framework of classical Formal Concept Analysis. As it is shown, all needed information is explicitly contained in a given formal fuzzy context and the proposed representation can be obtained without a creation of the corresponding fuzzy concept lattice.

Rough Fuzzy Concept Analysis

2017 ◽  
Vol 156 (2) ◽  
pp. 141-168 ◽  
Author(s):  
Eduard Bartl ◽  
Jan Konecny
Keyword(s):  
Concept Analysis ◽  
Fuzzy Concept

A context model for fuzzy concept analysis based upon modal logic

2004 ◽  
Vol 160 (1-4) ◽  
pp. 111-129 ◽  
Author(s):  
V.N. Huynh ◽  
Y. Nakamori ◽  
T.B. Ho ◽  
G. Resconi
Keyword(s):  
Modal Logic ◽  
Concept Analysis ◽  
Context Model ◽  
Fuzzy Concept

On biconcepts in formal fuzzy concept analysis

2017 ◽  
Vol 375 ◽  
pp. 16-29 ◽  
Author(s):  
Jan Konecny ◽  
Ondrej Krídlo
Keyword(s):  
Concept Analysis ◽  
Fuzzy Concept ◽  
Formal Fuzzy Concept
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