A novel method for destabilization of terrorist network

2020 ◽  
Vol 34 (27) ◽  
pp. 2050298
Author(s):  
Saurabh Singh ◽  
Shashi Kant Verma ◽  
Akhilesh Tiwari
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Research Area ◽  
Terrorist Group ◽  
Government Agencies ◽  
Multi Criteria Decision Making ◽  
Criminal Network ◽  
Relational Analysis ◽  
Novel Method ◽  
Grey Relational

Criminal network investigation is an ignited research area nowadays. There are several types of criminal network. Terrorist network is one of them. Exploring terrorist network is a demand of several investigating agencies. Different properties of network can be better considered to probe network properly using multi criteria decision-making methods. Grey Relational Analysis (GRA) method is a structural technique for organizing and analyzing complex decisions based on typical mathematics. This process can be employed for analyzing available datasets and designing useful conclusions. If network is explored and visualized, it can be destabilized efficiently. Identified members can be studied and thus their future actions can be prevented. These generalized designs can be used by government agencies for destabilization of terrorist group. This system is especially useful for countries like India that face a constant threat from various group of terrorists. This generalization can further be used to destabilize various criminal networks and their activities can be prevented. Thus, life and property of individuals can be saved.

A New Method of Multi-Attribute Decision-Making Based on Grey Relational Analysis with Time Series

2013 ◽  
Vol 444-445 ◽  
pp. 666-670
Author(s):  
Yi Zhang
Keyword(s):  
Decision Making ◽  
Time Series ◽  
Grey Relational Analysis ◽  
Uncertain Information ◽  
Decision Method ◽  
Rational Decision Making ◽  
Relational Analysis ◽  
Multi Attribute Decision Making ◽  
Subjective Views ◽  
Grey Relational

For the multi-attribute decision making with time series, based on the comprehensive consideration of various indicators of quality and growth degree, with grey relational analysis on less data, uncertain information can be integrated comparison, so we put forward a new decision method considering the decision maker subjective views, and provide a scientific and rational decision-making method. By the example, that method is viable.

scholarly journals A comparison of TOPSIS, grey relational analysis and COPRAS methods for machine selection problem in the food industry of Turkey

2021 ◽  
Vol 9 (2) ◽  
pp. 81
Author(s):  
Sami Özcan ◽  
Ali Kemal Çelik
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Entropy Method ◽  
Sensitivity Analyses ◽  
Food Sector ◽  
Relational Analysis ◽  
Machine Selection ◽  
Order Preference ◽  
Topsis Technique ◽  
Grey Relational

<div data-canvas-width="540.0693333333334">The paper aims to compare the results of the selection/choice of cream separators by using multi-criteria decision-making methods in an integrated manner for an enterprise with a dairy processing capacity of 80 to 100 tons per day operating in the Turkish food sector. A total of 7 alternative products and 7 criteria for milk processing were determined. Criterion weights were calculated using entropy method and then integrated into TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions), GRA (Grey Relational Analysis) and COPRAS (Complex Proportional Assessment) methods. Sensitivity analyses were carried out on the results obtained from the three methods to check for their reliability. At the end of the study, similar alternative and appropriate results were found from the TOPSIS and COPRAS methods. However, different alternative but appropriate or suitable results were obtained from the GRA method. Sensitivity analysis of the three methods showed that all the methods used were valid. In the review of available and related literature, very few studies on machine selection in the dairy and food sector in general were found. For this reason, it is thought that the study will contribute to the decision-making process of companies in the dairy sector in their choice of machinery selections. As far as is known, this paper is the first attempt in extant literature to compare in an integrated manner the results of TOPSIS, COPRAS and GRA methods considered in the study.</div>

scholarly journals Uma abordagem de decisão multi-critério para preempção de caminhos de luz em EON

2020 ◽  
Author(s):  
Alex Silva Santos ◽  
Gustavo Bittencourt Figueiredo
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
National Science Foundation ◽  
Analytical Hierarchical Process ◽  
Relational Analysis ◽  
National Science ◽  
Multi Attribute Decision Making ◽  
Grey Relational

Redes ópticas elásticas possuem a capacidade de oferecer largura próxima da solicitada pelo cliente. O que permite tal característica é a baixa granularidade dos recursos espectrais. Na degradação de serviço, requisições podem receber largura de banda menor que a solicitada. No entanto, situação onde não há opções de caminhos de luz para realizar a degradação é uma limitação para esta abordagem. Outra abordagem que pode ser adotada para liberar recursos ópticos é a realização de preempção dos caminhos de luz, os quais possuem diferentes requerimentos de qualidade de serviço (QoS). Tais parâmetros de QoS devem ser levados em consideração quando a preempção é realizada e a escolha de qual caminho de luz deve sofrer preempção se torna um problema de tomada de decisão multi-critério. Nós propomos um algoritmo que utiliza a técnica hybrid Multi-Attribute Decision Making (MADM) para realizar preempção de caminhos de luz em EON. Esta técnica é composta pelo Analytical Hierarchical Process (AHP) e Grey Relational Analysis (GRA). Simulações foram realizada na topologia de rede national science foundation network (NSFNET) para avaliar o algoritmo proposto. Os resultados mostraram que a abordagem proposta foi capaz de reduzir a probabilidade de bloqueio das classes de serviço com maior prioridade.

scholarly journals Multi-attribute decision making parametric optimization in two-stage hot cascade vortex tube through grey relational analysis

2020 ◽  
Vol 11 ◽  
pp. 21
Author(s):  
Racharla Madhu Kumar ◽  
NVVS Sudheer ◽  
Katam Ganesh Babu
Keyword(s):  
Decision Making ◽  
Grey Relational Analysis ◽  
Vortex Tube ◽  
Outlet Temperature ◽  
Point Temperature ◽  
Relational Analysis ◽  
Input Parameters ◽  
Multi Attribute Decision Making ◽  
Spot Cooling ◽  
Grey Relational

By setting two vortex tubes in hot cascade type Vortex tube manner, can achieve two cooling points for spot cooling applications with the single input. These cooling points play a vital role to cool tools in machining operations. The present work aims to optimize the output parameters such as outlet temperature, Coefficient of Performance (COP). Based on the literature, the performance of this vortex tube mainly depends on its input parameters such as air inlet pressure, length to diameter ratio, and the number of nozzles. In the present work, the above input parameters have been experimented on this vortex tube, based on the Taguchi L18 array. The optimal condition for both temperatures, COP at hot and cold outlets was calculated using grey relational analysis (GRA). The obtained experimental results were analyzed using the ANOVA approach. Also for multi responses, 1st and 2nd order predicted mathematical models developed by using Minitab 18 software and its accuracy checked. The achieved results are at first spot cooling point temperature 294.9 K, COPc1 as 0.0203, second spot cooling point temperature 284.2 K, and COPc2 as 0.1628. This work proved that for solving multi-attribute decision-making problems, grey relational analysis methodology was efficient.

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