A framework for rule-base evidential reasoning in the interval setting applied to diagnosing type 2 diabetes

Sevastianov, P.; Dymova, Ludmila; Bartosiewicz, Paweł

doi:10.1016/j.eswa.2011.09.115

Cited by 37 publications

(21 citation statements)

References 42 publications

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“…Section 3 presents a new approach to the rule-base evidential reasoning which makes it possible to use an information of values of all membership functions representing the intersecting (competing) fuzzy classes in the fuzzy logic rules. Based on real-world examples of type 2 diabetes diagnostics, we have shown that the new approach provides reasonable and intuitively obvious results in the cases when the known approaches (see [6,7,18,19]) lead to the controversial or wrong results. Finally the concluding section summarises the paper.…”

Section: Introductionmentioning

confidence: 91%

“…Therefore, the diagnosis Pre-diabetes in the spirit of DST can be treated as the compound hypothesis (H,D). Based on the known approaches to the rule-base evidential reasoning ( [6,19]) we get the following rules: Fig.1) using the above rules (3) and the conventional fuzzy logic, from the first test we get the diagnosis H (with m * Since these two tests are different sources of evidence, to obtain the final diagnosis they should be combined using an appropriate combination rule. Nevertheless, the use of classical fuzzy logic may lead to the counterintuitive results.…”

Section: Fig 1 Test 1 (Blood Glucose X1) and Test 2 (Blood Glucose X2)mentioning

confidence: 99%

“…In our papers [6,7,18,19], we have developed the method based on the synthesis of fuzzy logic and the Dempster-Shafer theory (DST ), which was used to the solution of some real-world decision making problems.…”

Section: Introductionmentioning

confidence: 99%

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A New Approach to the Rule-Base Evidential Reasoning with Application

Sevastjanov

Dymova

Kaczmarek

2015

Artificial Intelligence and Soft Computing

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Abstract. In this paper, a new approach to the rule-base evidential reasoning (RBER) based on a new formulation of fuzzy rules is presented. We have shown that the traditional fuzzy logic rules lose an important information when dealing with the intersecting fuzzy classes, e.g., such as Low and Medium, and this property may lead to the controversial results. In the framework of our approach, an information of the values of all membership functions representing the intersecting (competing) fuzzy classes is preserved and used in the fuzzy logic rules. As RBER methods are based on the synthesis of fuzzy logic and the Dempster-Shafer theory of evidence (DST ), the problem of the combination of basic probability assignments (bpas) from different sources of evidence arises. The classical Dempster's rule of combination is usually used for this purpose. The classical Dempster's rule may provide controversial results in the case of great conflict and is not idempotent one. We show that the Dempster's rule may provide unreasonable results not only in the case of large conflict, but in the case of complete absence of conflict, too. At the end, we show that in the cases of small and large conflict, the use of simple averaging rule for combination of bpas seems to be a best choice. The developed approach is illustrated by the solution of simple, but real-world problem of diagnostics of type 2 diabetes.

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Section: Introductionmentioning

confidence: 91%

Section: Fig 1 Test 1 (Blood Glucose X1) and Test 2 (Blood Glucose X2)mentioning

confidence: 99%

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A New Approach to the Rule-Base Evidential Reasoning with Application

Sevastjanov

Dymova

Kaczmarek

2015

Artificial Intelligence and Soft Computing

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“…In [11,13,17], a new approach free of both above mentioned restrictions was developed and used for the solution of real-world problems.…”

Section: Introductionmentioning

confidence: 99%

The Use of Intuitionistic Fuzzy Values in Rule-Base Evidential Reasoning

Dymova

Sevastjanov

Tkacz

2013

Artificial Intelligence and Soft Computing

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Abstract.A new approach to the rule-base evidential reasoning based on the synthesis of fuzzy logic, Atannasov's intuitionistic fuzzy sets theory and the Dempster-Shafer theory of evidence is proposed. It is shown that the use of intuitionistic fuzzy values and the classical operations on them directly may provide counter-intuitive results. Therefore, an interpretation of intuitionistic fuzzy values in the framework of DempsterShafer theory is proposed and used in the evidential reasoning. Using the real-world example, it is shown that such an approach provides reasonable and intuitively obvious results when the classical method of rule-base evidential reasoning cannot produce any reasonable results.

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“…(Ref. 12) discussed that there are two restrictions in the RIMER approach. One of them is that the RIMER approach did not provide the combination method of different evidence.…”

Section: Introductionmentioning

confidence: 99%

The Evidential Reasoning Approach to Medical Diagnosis using Intuitionistic Fuzzy Dempster-Shafer Theory

Wang¹,

Chen²,

Meng³

2014

International Journal of Computational Intelligence Systems

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For medical diagnosis, fuzzy Dempster-Shafer theory is extended to model domain knowledge under probabilistic and fuzzy uncertainty. However, there are some information loss using discrete fuzzy sets and traditional matching degree method. This study aims to provide a new evidential structure to reduce information loss. This paper proposes a new intuitionistic fuzzy evidential reasoning (IFER) approach which combines intuitionistic trapezoidal fuzzy numbers and inclusion measure to improve the accuracy of representation and reasoning. The proposed approach has been validated by a stroke diagnosis. It is shown that the IFER approach leads to more accurate results.

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A framework for rule-base evidential reasoning in the interval setting applied to diagnosing type 2 diabetes

Cited by 37 publications

References 42 publications

A New Approach to the Rule-Base Evidential Reasoning with Application

A New Approach to the Rule-Base Evidential Reasoning with Application

The Use of Intuitionistic Fuzzy Values in Rule-Base Evidential Reasoning

The Evidential Reasoning Approach to Medical Diagnosis using Intuitionistic Fuzzy Dempster-Shafer Theory

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