Mediative Fuzzy Extension Technique and Its Consistent Measurement in the Decision Making of Medical Application

Sharma, Manoj; Dhiman, Nitesh; Mishra, Lakshmi Narayan; Mishra, Vishnu Narayan; Sahani, Suresh Kumar

doi:10.1155/2021/5530681

Cited by 10 publications

(5 citation statements)

References 17 publications

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“…Using properties (28) and ( 29) matrices 𝜇 𝐵 ̃ * 𝑖 (𝐷) and 𝜇′ 𝐵 ̃ * 𝑖 (𝐷) are obtained, after aggregating and normalizing matrix 𝜇 𝐵 ̃𝑜 * 𝑖 (𝐷) is obtained.…”

Section: Determination Ofmentioning

confidence: 99%

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Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Kumar,

Sharma

2024

Preprint

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Multi-criteria decision making (MCDM) is introduced using trapezoidal vague numbers (TVNs) in medicine. Initially concepts of centroid and signed distance are generalized for TVNs. We also provide some desirable properties of the proposed distance measure. The decision making involves the medical diagnostic problem to reduce the vagueness and non-specificity from its environment. In this MCDM, each symptom is classified into some criteria. States of the patients, weights for the existing symptoms are assumed as vague point entries and relations of symptom criteria and diseases are considered using trapezoidal vague number entries. The usefulness of the developed approach is when it shows its capability and validity of the delivery. A numerical computation is illustrated with the whole procedure of the decision making. To show the capability and distinctness of the proposed methodology, a comparative discussion for outcomes is given with pre existing method. Present method coincides with existing fuzzy based method for the initial diagnosis while possibility differences for patient P1 and patient P2 range from 1–16.3% by the method based on existing traditionally fuzzy approach and in present approach these differences range from 2.15–7.46%. In the present approach, addition to the membership, another function called non membership is taken that contributes the upper bound of membership. Between these two memberships the hesitation part is dealt sophisticatedly. Also consideration of trapezoidal vague number as membership grade than the point estimation handles the blur cloud of association effectively.

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Section: Determination Ofmentioning

confidence: 99%

“…Mancilla et al optimized fuzzy logic controllers for bio-inspired algorithms [23]. Sharma et al extends diagnostic approach to investigate the medical diagnosis [28]. Mancilla et al designed fuzzy controller for optimization of autonomous robot path tracking [24].…”

Section: Related Workmentioning

confidence: 99%

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Kumar,

Sharma

2024

Preprint

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“…This initial proposal was only for type-1 fuzzy logic and was viewed as an extension of intuitionistic fuzzy logic. Later, other authors have applied this concept to several medical problems, such as heart disease diagnosis [5,6], diabetes diagnosis [7], prediction of the COVID-19 pandemic [8] and others [9]. In summary, most of the existing works utilizing MFL have been carried out in relation to the medical diagnosis area, where the knowledge of several medical experts is combined to improve the diagnosis.…”

Section: Introductionmentioning

confidence: 99%

Proposal for Mediative Fuzzy Control: From Type-1 to Type-3

Castillo,

Melin

2023

Symmetry

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This paper presents an initial proposal for the utilization of mediative fuzzy logic in control problems. Mediative fuzzy logic (MFL) was originally proposed with the idea of modeling situations in which there exists contradictory knowledge among several experts in an application domain. In this situation, a mediative solution may be a better choice in this particular decision-making situation. In this paper, we are extending the concept of fuzzy control to the realm of MFL for situations in which we have two or more control experts, and the design of the fuzzy controller has to be based on their knowledge. In this situation, we are taking advantage of the symmetrical nature of membership functions in reducing the complexity of designing the fuzzy controllers. The goal of this study was to improve control results by combining the knowledge of several experts, which MFL is aimed at executing. The initial architecture of mediative fuzzy control for type-1 fuzzy logic is presented, and an illustrative example is used to better comprehend the proposed approach. Later, we extend type-1 MFL to the realms of type-2 and type-3 fuzzy logic, and we also provide a comparative study that exhibits that the type-3 version surpasses the type-2 and type-1 versions of mediative fuzzy control. The idea of utilizing type-2 and type-3 is to improve the capabilities of the fuzzy controller in handling uncertainty coming from noise in the control process.

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“…Many extended techniques of fuzzy logic, such as intuitionistic fuzzy logic [13,14] and mediative fuzzy logic [15], have also been used in engineering and agricultural fields and the medical field [16,17]. Mediative fuzzy logic is also applied in the extension technique [18] for consistent measurement in decision making. The concept of the Z-number is very closely related to the idea of linguistic terms [19].…”

Section: Introductionmentioning

confidence: 99%

On Z-Intuitionistic Fuzzy Fractional Valuations for Medical Diagnosis: An Intuitionistic Fuzzy Knowledge-Based Expert System

et al. 2022

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In an uncertain situation, data may present in continuous form or discrete form. We have various techniques to deal with continuous data in a realistic situation. However, when data are in discrete form, the existing techniques are inadequate to deal with these situations, and these techniques cannot provide the proper modulation for adequate analysis of the system. In order to provide the proper acceleration to discrete data, we need an appropriate modulation technique that can help us to handle unconditional boundedness on the technique and will operate like the techniques used for continuous data with fractional variables. In this work, we developed an intuitionistic fuzzy fractional knowledge-based expert system using unconditional and qualified fuzzy propositions based on the Z-intuitionistic fuzzy fractional valuation probability density function. In this proposed method, the discrete fractional variables will be converted into intuitionistic fuzzy fractional numbers and then be used in our algorithm. The proposed Z-intuitionistic fuzzy fractional valuation knowledge-based system can easily be applied in the medical field for the diagnosis of diseases in a vague environment due to the ordered-pair characteristics of the Z-intuitionistic fuzzy fractional valuation. In this study, we collected data of dengue patients, which included seven clinical findings: Temperature, sugar, Pulse Rate (PR), age, cough, and Blood Pressure (BP). A numerical example was also carried out to elaborate on the present technique. In addition, a comparative study is discussed in this work. We also provide the managerial implications of the data, with the limitations of the proposed technique presented at the end of this work.

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Mediative Fuzzy Extension Technique and Its Consistent Measurement in the Decision Making of Medical Application

Cited by 10 publications

References 17 publications

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Generalized Fuzzy Technique and Its Consistent Assessment in Multi-criteria Decision Making of Medical Decisions

Proposal for Mediative Fuzzy Control: From Type-1 to Type-3

On Z-Intuitionistic Fuzzy Fractional Valuations for Medical Diagnosis: An Intuitionistic Fuzzy Knowledge-Based Expert System

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