Methods of knowledge representation using type-1 fuzzy sets

2008 ◽  
pp. 63-153
Keyword(s):  
Knowledge Representation ◽  
Fuzzy Sets

Type 2 Fuzzy Sets: An Appraisal of Theory and Applications

1998 ◽  
Vol 06 (06) ◽  
pp. 563-576 ◽  
Author(s):  
Robert John
Keyword(s):  
Knowledge Representation ◽  
Fuzzy Sets ◽  
Worked Examples

This paper provides a guide and tutorial to type 2 fuzzy sets. Type 2 fuzzy sets allow for linguistic grades of membership thus assisting in knowledge representation. They also offer improvement on inferencing with type 1 sets. The various approaches to knowledge representation and inferencing are discussed, with worked examples, and some of the applications of type 2 sets are reported.

An interval type-2 hesitant fuzzy best-worst method

2021 ◽  
pp. 1-28
Author(s):  
Ashraf Norouzi ◽  
Hossein Razavi hajiagha
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Group Decision Making ◽  
Group Decision ◽  
Fuzzy Ahp ◽  
Uncertain Data ◽  
Interval Type ◽  
Best Worst Method

Multi criteria decision-making problems are usually encounter implicit, vague and uncertain data. Interval type-2 fuzzy sets (IT2FS) are widely used to develop various MCDM techniques especially for cases with uncertain linguistic approximation. However, there are few researches that extend IT2FS-based MCDM techniques into qualitative and group decision-making environment. The present study aims to adopt a combination of hesitant and interval type-2 fuzzy sets to develop an extension of Best-Worst method (BWM). The proposed approach provides a flexible and convenient way to depict the experts’ hesitant opinions especially in group decision-making context through a straightforward procedure. The proposed approach is called IT2HF-BWM. Some numerical case studies from literature have been used to provide illustrations about the feasibility and effectiveness of our proposed approach. Besides, a comparative analysis with an interval type-2 fuzzy AHP is carried out to evaluate the results of our proposed approach. In each case, the consistency ratio was calculated to determine the reliability of results. The findings imply that the proposed approach not only provides acceptable results but also outperforms the traditional BWM and its type-1 fuzzy extension.

Centroids of Type-1 and Type-2 Fuzzy Sets When Membership Functions Have Spikes

2014 ◽  
Vol 22 (3) ◽  
pp. 685-692 ◽  
Author(s):  
Janet Aisbett ◽  
John T. Rickard
Keyword(s):  
Fuzzy Sets ◽  
Membership Functions

An interval type-2 fuzzy ANP approach to evaluate enterprise technological innovation ability

Kybernetes ◽  
2016 ◽  
Vol 45 (9) ◽  
pp. 1486-1500 ◽  
Author(s):  
Tong Wu ◽  
Xinwang Liu
Keyword(s):  
Fuzzy Sets ◽  
Evaluation Model ◽  
Influence Factors ◽  
Content Type ◽  
Fuzzy Anp ◽  
Enterprise Technology ◽  
Innovation Ability ◽  
Interval Type

Purpose The purpose of this paper is to overcome the drawbacks of analytic hierarchy process in solving complex decision-making problems, especially for the evaluation of enterprise technology innovation ability (ETIA). Because interval type-2 fuzzy sets (IT2 FSs) can handle uncertainty linguistic variables in a more flexible and precise way than type-1 fuzzy sets with their second fuzzy membership functions, a fuzzy ANP method with IT2 FSs is proposed to evaluate the ETIA. Design/methodology/approach The criteria of evaluation on ETIA are identified and an evaluation model for ETIA is constructed on the basis of the application analysis of ETIA and theoretical design of ANP. In addition, two different ranking methods of IT2 FSs are applied in processing the relationships between influence factors of ETIA. Findings By using the proposed interval type-2 fuzzy ANP (IT2 FANP) method, the efficiencies of the whole evaluation of ETIA can be measured and the important factors in the ETIA can also be determined. Compared with the type-1 FANP through the ranking results, the proposed IT2 FANP is more reasonable and robust for the evaluation of ETIA. Practical implications The proposed IT2 FANP method is applied on the evaluation of ETIA. With respect to the application, the proposed method can be used to evaluate many more complex problems that contain feedback and circular relationships. Originality/value The proposed IT2 FANP approach can solve the complexities and uncertainties at the same time. Considering the subjective initiative of decision-makers and the feedback between influence factors, the proposed method is more efficient than the existing type-1 approaches in the literature.

INTEGRATION OF MODAL AND FUZZY METHODS OF KNOWLEDGE REPRESENTATION IN ARTIFICIAL AGENTS

2013 ◽  
Vol 23 (01) ◽  
pp. 13-29 ◽  
Author(s):  
RADOSLAW P. KATARZYNIAK ◽  
GRZEGORZ POPEK
Keyword(s):  
Knowledge Representation ◽  
Fuzzy Sets ◽  
Common Sense ◽  
Artificial Agents ◽  
Cognitive Agents ◽  
Fuzzy Methods ◽  
The Common ◽  
Fuzzy Linguistic ◽  
Cognitive Attitude

To enable artificial systems to meaningfully use a semantic language of communication is one of the long-term and key targets not only in the field of artificial cognitive agents, but also of AI research in general. Given existing solutions for grounding of modal statements of a language of communication and an idea to model internal concepts of the agent as zadehian fuzzy-linguistic concepts, this paper shows how to meaningfully combine the two within a single framework. An accomplished goal is a model for grounding of modal and non-modal statements of a language of communication based on concepts modelled internally as fuzzy sets spanned over the domain of observation. This paper describes a way in which fuzzy-linguistic concepts are activated by perceptual inputs and how an agents grounds respective non-modal statements. Further, an agent supposed to describe an unobserved part of the environment can use autoepistemic operators of possibility, belief, and knowledge to describe its cognitive attitude toward it. It is discussed how the modal extensions of statements with fuzzy-linguistic concepts should be grounded in order to preserve the common-sense. The resulting constraints put on the model of grounding are formally represented in a form of analytical restrictions put on the so-called relation of epistemic satisfaction.

scholarly journals ASSESSMENT AND MANAGEMENT OF SAFETY RISKS THROUGH HIERARCHICAL ANALYSIS IN FUZZY SETS TYPE 1 AND TYPE 2: A CASE STUDY (FARYAB CHROMITE UNDERGROUND MINES)

2021 ◽  
Vol 36 (3) ◽  
pp. 1-17
Author(s):  
Mohammad Reza Ameri Siahuei ◽  
Mohammad Ataei ◽  
Ramin Rafiee ◽  
Farhang Sereshki
Keyword(s):  
Risk Assessment ◽  
Fuzzy Sets ◽  
Underground Mine ◽  
Underground Mines ◽  
Mine Safety ◽  
Safety Risks ◽  
Proper Scaling ◽  
Blast Scaling

There is a high rate of casualty among miners in the world every year. One way to reduce accidents and increase safety in mines is to use the risk management process to identify and respond to major hazards in mines. The present study is an attempt to investigate the assessment and management of safety risks in Faryab chromite underground mines. In this paper, the method of AHP in type-1 and type-2 fuzzy sets is used for risk assessment. Upon studying two underground mines of Faryab chromite (Makran and Nemat), 45 hazards were divided into 9 groups, among which 7 main risks were eventually identified. The risk assessment showed that the most important hazards in the Nemat underground mine are the required airflow, the lack of proper scaling and post-blast scaling. Similarly, the assessment of hazards in the Makran underground mine showed that post-blast scaling, absence of proper scaling, and proper ventilation of dust, are the most important hazards. Finally, after detecting the causes of the accidents, based on the records of accidents at the mine safety, health, and environmental unit, technical personnel’s descriptions, and similar risk projects, proper responses are prepared for each group of hazards.

scholarly journals Type-2 Fuzzy Expert System Approach for Decision-Making of Financial Assets and Investing under Different Uncertainty

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Zuzana Janková ◽  
Petr Dostál
Keyword(s):  
Time Series ◽  
Fuzzy Logic ◽  
Stock Market ◽  
Fuzzy Sets ◽  
Financial Time Series ◽  
Fuzzy Model ◽  
Exchange Traded Funds ◽  
International Equity Markets

Extensive research results of stock market time series using classical fuzzy sets (type-1) are available in the literature. However, type-1 fuzzy sets cannot fully capture the uncertainty associated with stock market developments due to their limited descriptiveness. This paper fills a scientific gap and focuses on type-2 fuzzy logic applied to stock markets. Type-2 fuzzy sets may include additional uncertainty resulting from unclear, uncertain, or inaccurate financial data through which model inputs are calculated. Here we propose four methods based on type-2 fuzzy logic, which differ in the level of uncertainty contained in fuzzy sets and compared with the type-1 fuzzy model. The case study aims to create a model to support investment decisions in Exchange-Traded Funds (ETFs) listed on international equity markets. The created models of type-2 fuzzy logic are compared with the classic type-1 fuzzy logic model. Based on the results of the comparison, it can be said that type-2 fuzzy logic with dual fuzzy sets is able to better describe data from financial time series and provides more accurate outputs. The results reflect the capability and effectiveness of the approach proposed in this document. However, the performance of type-2 fuzzy logic models decreases with the inclusion of increasing uncertainty in fuzzy sets. For further research, it would be appropriate to examine the different levels of uncertainty in the input parameters themselves and monitor the performance of such a modified model.

Multi-criteria decision-making method based on type-2 fuzzy sets

Filomat ◽  
2017 ◽  
Vol 31 (2) ◽  
pp. 431-450 ◽  
Author(s):  
Jing Wang ◽  
Qing-Hui Chen ◽  
Hong-Yu Zhang ◽  
Xiao-Hong Chen ◽  
Jian-Qiang Wang
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Computational Models ◽  
Fuzzy Numbers ◽  
Multi Criteria Decision Making ◽  
Interval Numbers ◽  
Interval Type ◽  
Uncertainty Information

Type-2 fuzzy sets (T2FSs) are the extension of type-1 fuzzy sets (T1FSs), which can convey more uncertainty information in solving multi-criteria decision-making (MCDM) problems. Motivated by the extension from interval numbers to triangular fuzzy numbers, three-trapezoidal-fuzzy-number-bounded type-2 fuzzy numbers (TT2FNs) are defined on the basis of interval type-2 trapezoidal fuzzy numbers (IT2TFNs), and they can convey more uncertainty information than T1FSs and IT2FSs. Moreover, the drawbacks of the existing computational models of generalized fuzzy numbers are analyzed, and a new computational model of fuzzy numbers is proposed, which is further extended to TT2FNs. Besides, a MCDM method is proposed to deal with the evaluation information given in the form of TT2FNs. Finally, an illustrative example and comparison analysis are provided to demonstrate the feasibility and validity of the proposed method.

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