A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

Abdullah, Lazim; Otheman, Adawiyah

doi:10.5815/ijisa.2013.02.03

Cited by 34 publications

(18 citation statements)

References 21 publications

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“…Weighing becomes an important issue to yield ranking such as the issue of weight update [6], new Entropy weight [7], Sensitivity-Simple Additive Weighting (S-SAW) [8], mutual weight [9]- [11].…”

Section: Related Workmentioning

confidence: 99%

The Decision Model for Selection of Tourism Site Using Analytic Network Process Method

Hadiwijaya¹,

Hamdani²,

Syafrianto³

et al. 2018

IJISA

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The criteria and sub criteria-based decision model for selection of tourism site using Analytic Network Process (ANP) method was to be implemented in Yogyakarta, Indonesia. In this study, we proposed criteria and sub criteria that influenced each other and had feedback between the two so that there was a comparison of tourism site alternatives according to sub criteria and pairwise comparative assessment with scale 1-9 that was then calculated in form of matrix of pairwise comparison. The result of this study was in form of decision alternatives in form of ranking to facilitate decision makers (DMs) in finding tourism sites.

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Section: Related Workmentioning

confidence: 99%

The Decision Model for Selection of Tourism Site Using Analytic Network Process Method

Hadiwijaya¹,

Hamdani²,

Syafrianto³

et al. 2018

IJISA

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“…For every x ϵ X, the value μ(x) is known as the grade of membership of x. We usually denote fuzzy set with membership values as       Membership function μ maps each element in X to a membership value between 0 and 1 [38]. There are three operational modules that constitute FCS.…”

Section: B Fuzzy Control System (Fcs)mentioning

confidence: 99%

Fuzzy-based User Behavior Characterization to Detect HTTP-GET Flood Attacks

Singh¹,

Singh²,

Kumar³

2018

IJISA

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Internet was designed to serve the basic requirement of data transfer between systems. The security perspectives were therefore overlooked due to which the Internet remains vulnerable to a variety of attacks. Among all the possible attacks, Distributed Denial of Service (DDoS) attack is one of the eminent threats that target the availability of the online services to the intended clients. Now-a-days, attackers target application layer of the network stack to orchestrate attacks having a high degree of sophistication. GET flood attacks have been very much prevalent in recent years primarily due to advancement of bots allowing impersonating legitimate client behavior. Differentiating between a human client and a bot is therefore necessary to mitigate an attack. This paper introduces a mitigation framework based on Fuzzy Control System that takes as input two novel detection parameters. These detection parameters make use of clients' behavioral characteristic to measure their respective legitimacy. We design an experimental setup that incorporates two widely used benchmark web logs (Clarknet and WorldCup) to build legitimate and attack datasets. Further, we use these datasets to assess the performance of the proposed through well-known evaluation metrics. The results obtained during this work point towards the efficiency of our proposed system to mitigate a wide range of GET flood attack types.

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“…A total of 82 papers were reviewed ranged from 2007 to April 2015. Our contributions to the literature are as follows: (1) to determine the MCDM approaches that have been integrated with IT2FSs, (2) to reveal application areas (education, energy, environment, healthcare, human resource management (HRM), investment management, manufacturing, risk management, technology management, transportation and logistics) that have further used these MCDM approaches based on IT2FSs, (3) to show the countries which published papers related to these MCDM approaches based on IT2FSs, and (4) to determine how the trend of type-2 fuzzy MCDM will continue in the future. The remainder of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive review of multi criteria decision making approaches based on interval type-2 fuzzy sets

Çelik

Gül

Aydın

et al. 2015

Knowledge-Based Systems

187

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A New Entropy Weight for Sub-Criteria in Interval Type-2 Fuzzy TOPSIS and Its Application

Cited by 34 publications

References 21 publications

The Decision Model for Selection of Tourism Site Using Analytic Network Process Method

The Decision Model for Selection of Tourism Site Using Analytic Network Process Method

Fuzzy-based User Behavior Characterization to Detect HTTP-GET Flood Attacks

A comprehensive review of multi criteria decision making approaches based on interval type-2 fuzzy sets

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