New membership function for poverty measure

Belhadj, Besma; Kaabi, Firas

doi:10.1111/meca.12297

Cited by 5 publications

(1 citation statement)

References 23 publications

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“…From a mathematics point of view, a membership function is a technique that implements for solving practical problems through experience instead of knowledge. Several membership functions are used by researchers such as Gaussian, trapezoidal, triangular and others [22]. Furthermore, the membership functions can be coupled with a conjunction operator, this situation is known as t-norms [23].…”

Section: The Membership Functionmentioning

confidence: 99%

Data Stream Clustering Using Fuzzy-based Evolving Cauchy Algorithm

Al-Khamees¹

2021

IJIES

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Many different applications in the real world can generate huge amount of data, that has unconventional features including massive size, fast access, besides the evolving in its nature; this is data stream. Data stream clustering algorithms began to grow at breakneck speed. evolving Cauchy (eCauchy) is a significant algorithm of density-based data stream clustering. The major limitation of eCauchy is the high number of clusters generated in dynamic environments. This paper presents an evolving model for data stream by optimizing e-Cauchy algorithm to decrease the number of clusters and reach to an ideal number by implementing evolving mechanisms (adding, merging, splitting clusters) based on a specific membership function. Model is tested by two real datasets NSL-KDD99 and keystroke. Proposed model outperforms two other algorithms, e-Cauchy and FEAC-Stream. Model constructs five and four clusters with less time to implement 1.30 and 2.30 minutes respectively for each dataset.

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Section: The Membership Functionmentioning

confidence: 99%

Data Stream Clustering Using Fuzzy-based Evolving Cauchy Algorithm

Al-Khamees¹

2021

IJIES

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CGPM: Poverty Mapping Framework Based on Multi-Modal Geographic Knowledge Integration and Macroscopic Social Network Mining

Zhao¹,

Gao²,

Chihsu³

et al. 2023

Lecture Notes in Computer Science

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Attributes inequality in multidimensional poverty measures fuzzy modeling

Belhadj

Bouanani

2022

Soft Comput

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Poverty is recently considered to be a multidimensional one. That is to say the poor can suffer multiple disadvantages at the same time. This paper aims to further develop and refine the multidimensional poverty measure using Fuzzy Sets Theory (FST). The application of FST starts with the choice of membership functions and the rules to manipulate to integrate attributes inequality in multidimensional poverty measure. An application based on individual well-being data from Tunisian households in 2015 is presented to illustrate use proposed concepts.

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New membership function for poverty measure

Cited by 5 publications

References 23 publications

Data Stream Clustering Using Fuzzy-based Evolving Cauchy Algorithm

Data Stream Clustering Using Fuzzy-based Evolving Cauchy Algorithm

CGPM: Poverty Mapping Framework Based on Multi-Modal Geographic Knowledge Integration and Macroscopic Social Network Mining

Attributes inequality in multidimensional poverty measures fuzzy modeling

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