scholarly journals Selection of solar tracking system using extended TOPSIS technique with interval type-2 pythagorean fuzzy numbers

2021 ◽  
Author(s):  
Rimsha Umer ◽  
Muhammad Touqeer ◽  
Abdullah Hisam Omar ◽  
Ali Ahmadian ◽  
Soheil Salahshour ◽  
...  
Keyword(s):  
Fuzzy Numbers ◽  
Tracking System ◽  
Weighted Averaging ◽  
Distance Method ◽  
Novel Approach ◽  
Solar Tracking ◽  
Interval Type ◽  
Topsis Technique ◽  
Pythagorean Fuzzy Numbers

AbstractThe Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is considered among the most frequently used techniques to deal with multi-criteria group decision-making (MCGDM) conflicts. In this article, we have presented an extended TOPSIS technique in the framework of interval type-2 trapezoidal Pythagorean fuzzy numbers (IT2TrPFN). We first projected a novel approach to evaluate the distance between them using ordered weighted averaging operator and $$(\alpha ,\beta )$$ ( α , β ) -cut. Subsequently, we widen the concept of TOPSIS method formed on the distance method with IT2TrPFNs and applied it on MCGDM dilemma by considering the attitudes and perspectives of the decision-makers. Lastly, an application of solar tracking system and numerous contrasts with the other existing techniques are presented to express the practicality and feasibility of our projected approach.

scholarly journals A novel extension of TOPSIS with interval type-2 trapezoidal neutrosophic numbers using $(\alpha,\beta,\gamma)$-Cuts

2021 ◽  
Author(s):  
Muhammad Touqeer ◽  
Rimsha Umer ◽  
Ali Ahmadian ◽  
Soheil salahshour
Keyword(s):  
Decision Makers ◽  
Decision Problems ◽  
Weighted Averaging ◽  
Owa Operator ◽  
Topsis Method ◽  
Ordered Weighted Averaging ◽  
Novel Approach ◽  
Order Preference ◽  
Interval Type

Multi-criteria decision-making (MCDM) is concerned with structuring and solving decision problems involving multiple criteria for decision-makers in vague and inadequate environment. The “Technique for Order Preference by Similarity to Ideal Solution” (TOPSIS) is one of the mainly used tactic to deal with MCDM setbacks. In this article, we put forward an extension of TOPSIS with interval type-2 trapezoidal neutrosophic numbers (IT2TrNNs) using the concept of (α, β, γ)-cut. First, we present a novel approach to compute the distance between two IT2TrNNs using ordered weighted averaging (OWA) operator and (α, β, γ)-cut. Subsequently, we broaden the TOPSIS method in the context of IT2TrNNs and implemented it on a MCDM problem. Lastly, a constructive demonstration and several contrasts with the other prevailing techniques are employed to articulate the practicability of the proposed technique. The presented strategy yields a flexible solution for MCDM problems by considering the attitudes and perspectives of the decision-makers.

Type–reduction of Interval Type–2 fuzzy numbers via the Chebyshev inequality

2021 ◽  
Author(s):  
Juan Carlos Figueroa-García ◽  
Heriberto Román-Flores ◽  
Yurilev Chalco-Cano
Keyword(s):  
Fuzzy Numbers ◽  
Chebyshev Inequality ◽  
Type Reduction ◽  
Interval Type

scholarly journals An Interval Type-2 Fuzzy Similarity-Based MABAC Approach for Patient-Centered Care

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 140 ◽  
Author(s):  
Junhua Hu ◽  
Panpan Chen ◽  
Yan Yang
Keyword(s):  
Fuzzy Numbers ◽  
Patient Centered Care ◽  
Integrated Medicine ◽  
Patient Centered ◽  
Fuzzy Similarity ◽  
Nursing Services ◽  
Centered Care ◽  
Type 2 Diabetes Treatment ◽  
Interval Type

Patient-centered care is an essential part of the implementation of integrated medicine, integrating humanistic care into nursing services, enhancing communication between caregivers and patients, and providing personalized service to patients. Based on the similarity of interval type-2 fuzzy numbers (IT2FNs), a novel similarity-based methodology is presented for the selection of the most suitable medical treatment under a patient-centered environment. First, we propose a new similarity based on the geometric properties of interval type-2 fuzzy numbers and present a new property based on the center of gravity. Meanwhile, in order to better highlight the advantages of the proposed similarity, we selected 30 samples for comparative experiments. Second, considering the straightforward logic of the multi-attributive border approximation area comparison (MABAC) method, we extended it based on similarity to make the decision more accurate. Finally, a realistic patient-centered type-2 diabetes treatment selection problem is presented to verify the practicality and effectiveness of the proposed algorithm. A comparative analysis with existing methods is also described.

scholarly journals Quadrilateral Interval Type-2 Fuzzy Regression Analysis for Data Outlier Detection

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Pingping Gao ◽  
Yabin Gao
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Outlier Detection ◽  
Euclidean Distance ◽  
Fuzzy Numbers ◽  
Fuzzy Regression ◽  
Fuzzy Regression Analysis ◽  
Fuzzy Regression Model ◽  
Interval Type

This paper presents a fuzzy regression analysis method based on a general quadrilateral interval type-2 fuzzy numbers, regarding the data outlier detection. The Euclidean distance for the general quadrilateral interval type-2 fuzzy numbers is provided. In the sense of Euclidean distance, some parameter estimation laws of the type-2 fuzzy linear regression model are designed. Then, the data outlier detection-oriented parameter estimation method is proposed using the data deletion-based type-2 fuzzy regression model. Moreover, based on the fuzzy regression model, by using the root mean squared error method, an impact evaluation rule is designed for detecting data outlier. An example is finally provided to validate the presented methods.

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