A ranking procedure of Murabahah applications using fuzzy inferior ratio with generalized fuzzy numbers

Ahmad, Sharifah Aniza Sayed; Mohamad, Dzulkifli; Azman, Nurul Iffah

doi:10.1063/5.0018457

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…The height of the membership and non-membership functions are determined by the confidence level, which has been decided by the decision-maker [30]. It is crucial to include the confidence level since decision-makers usually come from various backgrounds, including those with different degrees of expertise, knowledge, and other characteristics that might influence the evaluation process [31].…”

Section: Determine the Confidence Level Of L-r Intuitionistic Fuzzy N...mentioning

confidence: 99%

A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification

Shafie,

Mohamad,

Awang Kechil

2023

Mal. J. Fund. Appl. Sci.

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A generalised L-R intuitionistic fuzzy numbers is an L-R intuitionistic fuzzy numbers that incorporates confidence level for both membership and non-membership functions. Therefore, this intuitionistic fuzzy number is suitable for classifying the river water pollution. This study aims to introduce the generalised L-R intuitionistic fuzzy numbers (GLRIFNs) which includes the membership and non-membership functions to classify the river water pollution using TOPSIS with CRITIC method. Due to the insufficient river data, this study has simulated the river data using the bootstrap method. This study had classified river water pollution for several rivers in Johor, Malaysia, namely Kim Kim River, Sayong River, Telor River, Pelepah River, and Bantang River from 2017 to 2021. The result shows that the Bantang River is the cleanest river, while the Kim Kim River is the most polluted river. The results proved that the GLRIFNs is quite a reliable method to classify river water pollution.

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Section: Determine the Confidence Level Of L-r Intuitionistic Fuzzy N...mentioning

confidence: 99%

A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification

Shafie,

Mohamad,

Awang Kechil

2023

Mal. J. Fund. Appl. Sci.

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“…Sharma, 2011) (Doda, 2013) (Sharma, 2014) and also some research on the structure of intuitionistic fuzzy (Annamalai, 2014;Atanassov, 1999c;Ejegwa et al, 2014). Some applications of intuitionistic fuzzy in other sets (Atanassov, 1999a;Kim & Jun, 2002;Marashdeh & Salleh, 2011) and in several fields other than mathematics, especially in decision making (Abdullah et al, 2020;Abdullah & Goh, 2019;Ahmad et al, 2020;Das et al, 2013;Maji et al, 2002;Şahin & Karabacak, 2020).…”

Section: Dian Pratama 41 Preliminarymentioning

confidence: 99%

Kernel Dan Sifatnya Pada Translasi Naik Dan Turun Ring Fuzzy Intuitionistik

Pratama

2022

Mathline

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Intuitionistic fuzzy ring is a generalized of ring combined with intuitionistic fuzzy sets. It also has impact on ideal so it become intuitionistic fuzzy ideal. The existence of the generalization process, needs to be studied about the properties of kernel at ring homomorphism in which we know that the kernel of a ring homomorphism is ideal. In addition, the study of fuzzy sets there are operators that are subject to membership and non membership functions. One of the known operators is up translates. This research examines the structure of the kernel at homomorphism rings in fuzzy intuitionistic rings. After that the structure of the kernel is also examined if the intuitionistic fuzzy ring is subjected to an up translates operator.

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A ranking procedure of Murabahah applications using fuzzy inferior ratio with generalized fuzzy numbers

Cited by 2 publications

References 9 publications

A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification

A Multi-Criteria Generalised L-R Intuitionistic Fuzzy TOPSIS with CRITIC for River Water Pollution Classification

Kernel Dan Sifatnya Pada Translasi Naik Dan Turun Ring Fuzzy Intuitionistik

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