Fuzzy CoCo: Balancing Accuracy and Interpretability of Fuzzy Models by Means of Coevolution

2003 ◽  
pp. 119-146 ◽  
Author(s):  
Carlos-Andrés Peña-Reyes ◽  
Moshe Sipper
Keyword(s):  
Fuzzy Models

ENVIRONMENTAL SUSTAINABILITY BASED ON FUZZY MODELS

2008 ◽  
Vol 7 (1) ◽  
pp. 25-29 ◽  
Author(s):  
Marius Pislaru* ◽  
Silvia Avasilcai ◽  
Alexandru Trandabat
Keyword(s):  
Environmental Sustainability ◽  
Fuzzy Models

Building Multi-Agent Systems With Reinforcement Hierarchical Neuro-Fuzzy Models

2016 ◽  
Author(s):  
Marcelo França Corrêa ◽  
Marley Vellasco ◽  
Karla Figueiredo
Keyword(s):  
Multi Agent Systems ◽  
Agent Systems ◽  
Fuzzy Models ◽  
Neuro Fuzzy ◽  
Multi Agent

scholarly journals Fuzzy Models of the Dangerous Situations Prediction

2021 ◽  
Vol 54 ◽  
pp. 12-22
Author(s):  
Vladimir Karetnikov ◽  
Anatoly Sazonov
Keyword(s):  
Fuzzy Models

A framework of decision making based on bipolar fuzzy competition hypergraphs

2021 ◽  
pp. 1-21
Author(s):  
Sundas Shahzadi ◽  
Areen Rasool ◽  
Musavarah Sarwar ◽  
Muhammad Akram
Keyword(s):  
Biological Sciences ◽  
Decision Making ◽  
Comparative Analysis ◽  
Social Networking ◽  
Real World ◽  
Fuzzy Models ◽  
New Concepts ◽  
Proposed Model ◽  
Business Market ◽  
Strength Of Competition

Bipolarity plays a key role in different domains such as technology, social networking and biological sciences for illustrating real-world phenomenon using bipolar fuzzy models. In this article, novel concepts of bipolar fuzzy competition hypergraphs are introduced and discuss the application of the proposed model. The main contribution is to illustrate different methods for the construction of bipolar fuzzy competition hypergraphs and their variants. Authors study various new concepts including bipolar fuzzy row hypergraphs, bipolar fuzzy column hypergraphs, bipolar fuzzy k-competition hypergraphs, bipolar fuzzy neighborhood hypergraphs and strong hyperedges. Besides, we develop some relations between bipolar fuzzy k-competition hypergraphs and bipolar fuzzy neighborhood hypergraphs. Moreover, authors design an algorithm to compute the strength of competition among companies in business market. A comparative analysis of the proposed model is discuss with the existing models such bipolar fuzzy competition graphs and fuzzy competition hypergraphs.

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