A Type of Score Function on Intuitionistic Fuzzy Sets with Double Parameters and Its application to Pattern Recognition and Medical Diagnosis

Zhen-hua, Zhang; Yang, Jingyu; Ye, Youpei; Hu, Yong; Zhang, Qiansheng

doi:10.1016/j.proeng.2012.01.667

Cited by 22 publications

(13 citation statements)

References 10 publications

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“…These results are consistent with the proposed model's results. Also, we observed that the fourth most suitable technology (PT 1 )with respect to Gümüş and Bali [24] and Zhang et al [35] results in Table 6 are the same as that of our model. The study not only revealed the suitability of the proposed model for ranking renewable energy technologies but reveals its suitability for selecting a reliability-based energy technology under a dynamic environment.…”

Section: Discussion Of Resultssupporting

confidence: 84%

“…Using a higher-the-better concept, Table 5 shows that these technologies can be ranked as follows: PT 5 > PT 2 > PT 3 > PT 4 > PT 1 . To validate this ranking order, the MCDM approaches in Liu et al [34], Zhang et al [35], and Gümüş and Bali [24] were used to solve the same problem. Table 6 shows these approaches results for the renewable energy technology problem.…”

Section: Discussion Of Resultsmentioning

confidence: 99%

“…Table 6 The technologies closeness coefficients and ranks Gümüş and Bali [24] Liuetal. [34] Zhang et al [35] S(r i ) R a n k i n g…”

Section: Compliance With Ethical Standardsmentioning

confidence: 99%

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Evaluation of Renewable Energy Technology Based on Reliability Attributes Using Hybrid Fuzzy Dynamic Decision-Making Model

Aikhuele

Ighravwe

Akinyele

2019

Technol Econ Smart Grids Sustain Energy

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Socio-technical and economic attributes consideration are very important during a renewable energy technology selection for a community. When decision-makers considered these attributes under a dynamic nature, they arrive at a robust decision. Hence, this study proposes an integrated model for renewable energy technologies evaluation under a dynamic condition. We developed the model using dynamic intuitionistic fuzzy Einstein geometric averaging operator, intuitionistic fuzzy entropy, and the intuitionistic fuzzy technique for order of preference by similarity to ideal solution method (TOPSIS). This model's applicability was tested using five renewable energy technologies-solar (PT 1), wind (PT 2), hydroelectricity (PT 3), geothermal (PT 4) and biomass (PT 5) and five attributes (risk factor, payback reliability, social benefit, change in demand and cost). Based on five energy experts, from academia and industry, opinions, the proposed model identified biomass energy technology as the most suitable energy technology. Three existing multi-criteria models were used to verify the proposed model; the proposed model performance was consistent with the existing models' results. From most suitable the least suitable, the model ranked these technologies PT 5 > PT 2 > PT 3 > PT 1 > PT 4 .

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Section: Discussion Of Resultssupporting

confidence: 84%

Section: Discussion Of Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of Renewable Energy Technology Based on Reliability Attributes Using Hybrid Fuzzy Dynamic Decision-Making Model

Aikhuele

Ighravwe

Akinyele

2019

Technol Econ Smart Grids Sustain Energy

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“…De et al [9] extended the Sanchez's method with the theory of intuitionistic fuzzy sets (IFSs). Samuel and Balamurugan [31], Szmidt and Kacprzyk [53], Zhang et al [71], Hung and Yang [19], Wang and Xin [63], Vlachos and Sergiadis [62], Zhang and Jiang [70], Wei and Ye [64] and Hung [18], Junjun et al [20], Maheshwari and Srivastava [24] continued to work on the IFS theory to improve the method of De et al [9], i.e., by using new score functions, new distance functions, or new measures instead of the score function in the method of De et al [9]. In this paper, the proposed algorithm combines the δ-equalities with the extended Sanchez's approach for intuitionistic fuzzy sets.…”

Section: Introductionmentioning

confidence: 99%

δ-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis

2017

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Intuitionistic fuzzy set is capable of handling uncertainty with counterpart falsities which exist in nature. Proximity measure is a convenient way to demonstrate impractical significance of values of memberships in the intuitionistic fuzzy set. However, the related works of In this paper, we examine this problem and propose new notions of δ-equalities for the intuitionistic fuzzy set and δ-equalities for intuitionistic fuzzy relations. Two fuzzy sets are said to be δ-equal if they are equal to an extent of δ. The applications of δ-equalities are important to fuzzy statistics and fuzzy reasoning. Several characteristics of δ-equalities that were not discussed in the previous works are also investigated. We apply the δ-equalities to the application of medical diagnosis to investigate a patient's diseases from symptoms. The idea is using δ-equalities for intuitionistic fuzzy relations to find groups of intuitionistic fuzzified set with certain equality or similar degrees then combining them. Numerical examples are given to illustrate validity of the proposed algorithm. Further, we conduct experiments on real medical datasets to check the efficiency and applicability on real-world problems. The results obtained are also better in comparison with 10 existing diagnosis methods namely De et al. (Fuzzy Sets

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“…Besides the aggregation operators on IVIFSs, many researchers devoted themselves to decision making with Atanassov's interval-valued intuitionistic fuzzy information [19][20][21][22][23] and applied the Atanassov's interval-valued intuitionistic fuzzy theory in many fields [24][25][26][27][28]. Although many multi-attribute decision making approaches with under Atanassov's interval-valued intuitionistic fuzzy information are researched, none of them consider the decision makers' risk attitudes.…”

Section: Introductionmentioning

confidence: 99%

An approach to Atanassov's interval-valued intuitionistic fuzzy multi-attribute decision making based on prospect theory

Meng¹,

Tan²,

Chen³

2015

IJCIS

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Prospect theory is a very effective method to express behavioral decision making under uncertainty. This paper attempts to develop a method to multi-attribute decision making with Atanassov's interval-valued intuitionistic fuzzy information using prospect theory. This method first transforms Atanassov's interval-valued intuitionistic fuzzy variables into the prospect values using the value function in prospect theory. Based on the aspiration levels, Atanassov's intuitionistic fuzzy prospect gain and loss matrices are obtained. Then, using the Atanassov's interval-valued intuitionistic hybrid weight averaging (IVIHWA) operator or the Atanassov's interval-valued intuitionistic hybrid Shapley weight averaging (IVIHSWA) operator, the comprehensive Atanassov's interval-valued intuitionistic fuzzy prospect value of each alternative is calculated. According to the comprehensive Atanassov's interval-valued intuitionistic fuzzy prospect values, a ranking method of alternatives is presented. Finally, two illustrative examples are selected to show the feasibility and availability of the proposed method.

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A Type of Score Function on Intuitionistic Fuzzy Sets with Double Parameters and Its application to Pattern Recognition and Medical Diagnosis

Cited by 22 publications

References 10 publications

Evaluation of Renewable Energy Technology Based on Reliability Attributes Using Hybrid Fuzzy Dynamic Decision-Making Model

Evaluation of Renewable Energy Technology Based on Reliability Attributes Using Hybrid Fuzzy Dynamic Decision-Making Model

δ-equality of intuitionistic fuzzy sets: a new proximity measure and applications in medical diagnosis

An approach to Atanassov's interval-valued intuitionistic fuzzy multi-attribute decision making based on prospect theory

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