An Intelligent Similarity Model between Generalized Trapezoidal Fuzzy Numbers in Large Scale

Tourad, Mohamedou Cheikh; Abdali, Abdelmounaïm

doi:10.5391/ijfis.2018.18.4.303

Cited by 5 publications

(6 citation statements)

References 19 publications

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“…with the flow of publication high online, a user risks finding the volume of information received excessive or unmanageable. We will work on the partial satisfaction between the items and the subscriptions based on the similarity measures [22].…”

Section: Discussionmentioning

confidence: 99%

A New Ranked-Key Structure for Intelligent Pub-Sub Systems in Large Scale

Tourad*,

Abdali

2019

IJEAT

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The rapid growth of information published on the net and the subsequent increase of the number of it users was the reason behind the discovery of Web syndication. The Pub/sub (Publish/Subscribe) system is the first and the most used system for web syndication. It allows the user to keep an eye on the development of the information that interested him. This information is managed by data collectors (RSS : Really Simple Syndication) in real time. Today, the development of new notifications systems is essential for the retrieval of specific information from the Big Data. In the present work, a new algorithm based on Ranked key is proposed. Such indexation allows the development of an efficient and an intelligent system.

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Section: Discussionmentioning

confidence: 99%

A New Ranked-Key Structure for Intelligent Pub-Sub Systems in Large Scale

Tourad*,

Abdali

2019

IJEAT

Self Cite

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“…Despite the plethora of distance metrics [5] to be had for deployment in the distance layer of Siamese models, including Euclidean distance and cosine similarity, the selection of the most appropriate metric stays critical to the achievement of the getting to know manner. In this context, the paintings introduces MCESTA [6], an innovative method that synergizes a couple of similarity metrics [5], every fine-tuned with taskprecise weights, to achieve superior performance in similarity mastering responsibilities. Through this composite metric machine, MCESTA seeks to set up a new benchmark in the discipline, imparting a flexible and sturdy way to the challenges of similarity measurement.…”

Section: Introductionmentioning

confidence: 99%

“…In the study, MCESTA is employed as a metric of similarity, representing a combination of three standard similarity metrics [6].…”

Section: Introductionmentioning

confidence: 99%

DeepSL: Deep Neural Network-based Similarity Learning

Tourad,

Abdelmounaim,

Dhleima

et al. 2024

IJACSA

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The quest for a top-rated similarity metric is inherently mission-specific, with no universally "great" metric relevant across all domain names. Notably, the efficacy of a similarity metric is regularly contingent on the character of the challenge and the characteristics of the records at hand. This paper introduces an innovative mathematical model called MCESTA, a versatile and effective technique designed to enhance similarity learning via the combination of multiple similarity functions. Each characteristic within it is assigned a selected weight, tailor-made to the necessities of the given project and data type. This adaptive weighting mechanism enables it to outperform conventional methods by providing an extra nuanced approach to measuring similarity. The technique demonstrates significant enhancements in numerous machine learning tasks, highlighting the adaptability and effectiveness of our model in diverse applications.

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“…A year later, the novel initiative of defining the MADA (Modified Area Development Approach) methodology based on a D number was explained in Mo and Deng ( 2018 ).Thereafter, Garg ( 2018 ) gave a new direction to decision-making processes, by developing an IFS-based cosine SM. Baccour ( 2018 ) pointed out some distance and SMs to aid the process of multicriteria decision-making; and likewise, Tourad and Abdali ( 2018 ) received recognition for devising an SM for GFNs and in a similar manner. Wei ( 2018 ) left no stone unturned, to develop a picture fuzzy set-based SM.…”

Section: Introductionmentioning

confidence: 99%

Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers

Dutta

Borah

2021

J Ambient Intell Human Comput

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Multicriteria Decision Making (MCDM) has a huge role to play while ruling out one suitable alternative among a pool of alternatives governed by predefined multiple criteria. Some of the factors like imprecision, lack of information/data, etc., which are present in traditional MCDM processes have showcased their lack of efficiency and hence eventually it has paved the ways for the development of Fuzzy multicriteria decision making (FMCDM). In FMCDM processes, the decision makers can model most of the real-life phenomena by fuzzy information-based preferences. The availability of a wide literature on similarity measure (SM) emphasizes the vital role of SM of generalized fuzzy numbers (GFNs) to conduct accurate and precise decision making in FMCDM problems. Despite having few advantages, most of the existing approaches possessed a certain degree of counter intuitiveness and discrepancies. Thus, we have attempted to propose a novel SM for generalized trapezoidal fuzzy numbers (GTrFNs) which could deliberately overcome the impediments associated with the earlier existing approaches. Moreover, a meticulous comparative study with the existing approaches is also presented. This paper provides us with an improved method to obtain the similarity values between GTrFNs and the proposed SM consists of calculating the prominent features of fuzzy numbers such as expected value and variance. We use fourteen different sets of GTrFNs, to compare the fruition of the present approach with the existing SM approaches. Furthermore, to show the utility and applicability of our proposed measure, we illustrate few practical scenarios such as the launching of an electronic gadget by a company, a problem of medical diagnosis and finally, a proper anti-virus mask selection in light of the recent COVID-19 pandemic. The obtained results with our proposed SM, for the mentioned FMCDM problems, are analytically correct and they depict the efficiency and novelty of the present article.

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An Intelligent Similarity Model between Generalized Trapezoidal Fuzzy Numbers in Large Scale

Cited by 5 publications

References 19 publications

A New Ranked-Key Structure for Intelligent Pub-Sub Systems in Large Scale

A New Ranked-Key Structure for Intelligent Pub-Sub Systems in Large Scale

DeepSL: Deep Neural Network-based Similarity Learning

Multicriteria decision making approach using an efficient novel similarity measure for generalized trapezoidal fuzzy numbers

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