Technology of Automated Medical Diagnostics Using Fuzzy Linguistic Variables and Consensus Ranking Methods

2009 ◽  
pp. 38-41
Author(s):  
A. I. Maistrou ◽  
A. V. Bogomolov
Keyword(s):  
Medical Diagnostics ◽  
Linguistic Variables ◽  
Ranking Methods ◽  
Fuzzy Linguistic

scholarly journals A Fuzzy Rule-Based Expert System for Evaluating Intellectual Capital

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Mohammad Hossein Fazel Zarandi ◽  
Neda Mohammadhasan ◽  
Susan Bastani
Keyword(s):  
Performance Evaluation ◽  
Expert System ◽  
Intellectual Capital ◽  
Fuzzy Rule ◽  
Qualitative Evaluation ◽  
Linguistic Variables ◽  
Rule Based ◽  
Proposed Model ◽  
Linguistic Approach ◽  
Fuzzy Linguistic

A fuzzy rule-based expert system is developed for evaluating intellectual capital. A fuzzy linguistic approach assists managers to understand and evaluate the level of each intellectual capital item. The proposed fuzzy rule-based expert system applies fuzzy linguistic variables to express the level of qualitative evaluation and criteria of experts. Feasibility of the proposed model is demonstrated by the result of intellectual capital performance evaluation for a sample company.

scholarly journals 5-Item Likert Scale and Percentage Scale Correspondence with Implications for the Use of Models with (Fuzzy) Linguistic Variables

2021 ◽  
Vol 31 ◽  
pp. 3-16
Author(s):  
Jiří Mazurek ◽  
Cristina Pérez Rico ◽  
Carlos Fernández García ◽  
Jean-Pierre Magnot ◽  
Tristan Magnot
Keyword(s):  
Decision Making ◽  
Czech Republic ◽  
Likert Scale ◽  
Linguistic Variables ◽  
The Czech Republic ◽  
Men And Women ◽  
Fuzzy Linguistic ◽  
Use Of Models

The aim of this paper is to examine how people perceive correspondence between the 5-item Likert scale and the percentage scale (the LS-PS correspondence thereinafter). Are all five items of the Likert scale equidistant? Do people use the same scale when evaluating different objects? Are men and women different? Are people from different countries / cultures different? The method of the study was a questionnaire with 661 participating respondents altogether from the Czech Republic, Ecuador, and France. The results indicate that the 5-item Likert scale is neither equidistant, nor symmetrical. Furthermore, there are (highly) statistically significant differences in the LS-PS correspondence with respect to location, age, or gender of respondents. The results can be used as an input for more precise decision-making modeling associated with (fuzzy) linguistic variables.

A Fuzzy Set Analysis of Skill, Rule and Knowledge-Based Workload

1988 ◽  
Vol 32 (2) ◽  
pp. 164-167 ◽  
Author(s):  
Neville Moray ◽  
Eugene Kruschelnicky ◽  
Paul Eisen ◽  
Laura Money ◽  
I. B. Turksen
Keyword(s):  
Task Difficulty ◽  
Linguistic Variables ◽  
Combination Rules ◽  
Rule Based ◽  
Fuzzy Measures ◽  
Knowledge Based ◽  
Fuzzy Set Analysis ◽  
Complete Set ◽  
Fuzzy Linguistic ◽  
Systematic Framework

Using fuzzy measures of task difficulty the effect of combining different aspects of a task on the overall task workload was explored. A complete set of combination rules is provided, of the general form “if the skill-based component is slightly difficult, the rule-based moderately difficult, and the knowledge-based slightly difficult, then the task as a whole is moderately difficult.” Fuzzy linguistic variables provide an adequate systematic framework for such combined judgments.

Fuzzy Knowledge Representation Based on Fuzzy Linguistic Variable Ontology and SWRL on the Semantic Web

2011 ◽  
Vol 58-60 ◽  
pp. 1707-1711
Author(s):  
Yan Ling Li ◽  
Yi Duo Liang ◽  
Jun Zhai
Keyword(s):  
Semantic Web ◽  
Knowledge Representation ◽  
Web Applications ◽  
Fuzzy Rule ◽  
Linguistic Variables ◽  
Semantic Relationships ◽  
Rule Management ◽  
Fuzzy Linguistic Variable ◽  
Fuzzy Linguistic ◽  
Fuzzy Knowledge

Ontology is adopted as a standard for knowledge representation on the Semantic Web, and Ontology Web Language (OWL) is used to add structure and meaning to web applications. In order to share and resue the fuzzy knowledge on the Semantic Web, we propose the fuzzy linguistic variables ontology (FLVO), which utilizes ontology to represent formally the fuzzy linguistic variables and defines the semantic relationships between fuzzy concepts. Then fuzzy rules are described in Semantic Web Rule Language (SWRL) on the basis of FLVO model. Taking a sample case for students’ performance in physics for example, the fuzzy rule management system is built by using the tool protégé and SWRLTab, which shows that this research enables distributed fuzzy applications on the Semantic Web.

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