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Soft Computing
Erschienen in: Soft Computing 14/2019

24.05.2018 | Methodologies and Application

Neyman–Pearson lemma based on intuitionistic fuzzy parameters

verfasst von: Mohammad Ghasem Akbari, Gholamreza Hesamian

Erschienen in: Soft Computing | Ausgabe 14/2019

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Abstract

The present work aims to extend the classical Neyman–Pearson lemma based on a random sample of exact observations to test intuitionistic fuzzy hypotheses. In this approach, we extend the concepts of type-I error, type-II and power of test. Some applied examples are provided to illustrate the proposed method. In addition, the proposed method is examined to be compared with an existing method.
Vorheriger Artikel Interval-based, nonparametric approach for resampling of fuzzy numbers
Nächster Artikel Applying various hybrid intelligent systems to evaluate and predict slope stability under static and dynamic conditions

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Metadaten
Titel
Neyman–Pearson lemma based on intuitionistic fuzzy parameters
verfasst von
Mohammad Ghasem Akbari
Gholamreza Hesamian
Publikationsdatum
24.05.2018
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 14/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3252-4

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