scholarly journals A novel risk ranking method based on the single valued neutrosophic set

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Kuei-Hu Chang
Keyword(s):  
Ranking Method ◽  
Neutrosophic Set ◽  
Risk Ranking

Priority setting for existing chemicals: European Union risk ranking method

1999 ◽  
Vol 18 (4) ◽  
pp. 772-779 ◽  
Author(s):  
Bjorn G. Hansen ◽  
Anniek G. van Haelst ◽  
Kees van Leeuwen ◽  
Peter van der Zandt
Keyword(s):  
European Union ◽  
Priority Setting ◽  
Ranking Method ◽  
Risk Ranking ◽  
Existing Chemicals

scholarly journals Evaluation of the Los Alamos Nuclear Material Packaging Risk Ranking Method

2021 ◽  
Author(s):  
Paul Smith ◽  
Elizabeth Kelly ◽  
Kimberly Kaufeld ◽  
Timothy Stone ◽  
David Prochnow ◽  
...  
Keyword(s):  
Nuclear Material ◽  
Ranking Method ◽  
Los Alamos ◽  
Risk Ranking

scholarly journals Prioritization of pesticides in crops with a semi-quantitative risk ranking method for Taiwan postmarket monitoring program

2019 ◽  
Vol 27 (1) ◽  
pp. 347-354 ◽  
Author(s):  
Wei-Chun Chou ◽  
Wei-Ren Tsai ◽  
Hsiu-Hui Chang ◽  
Shui-Yuan Lu ◽  
King-Fu Lin ◽  
...  
Keyword(s):  
Monitoring Program ◽  
Ranking Method ◽  
Risk Ranking

scholarly journals Analysis of the Risks arising from Fire Installations in Workplaces using the Ranking Method

2020 ◽  
Vol 10 (4) ◽  
pp. 5914-5920
Author(s):  
F. Yilmaz ◽  
S. Alp ◽  
B. Oz ◽  
A. Alkoc
Keyword(s):  
Risk Assessment ◽  
Risk Analysis ◽  
Fire Safety ◽  
Fuzzy Ahp ◽  
Fire Risk ◽  
Ranking Method ◽  
Analysis Method ◽  
Safety Factors ◽  
Risk Ranking ◽  
Work Area

The aim of this study is to analyze the risks arising from fire installations in workplaces. It also aims to propose a risk analysis method in the form of a “Fire Safety Risk Ranking System” for enterprises with a closed work area of more than 1000m2 in accordance with regulations in Turkey. The relative weights of fire safety factors were determined by Fuzzy AHP. The ranking points of the enterprises were calculated by using the weights obtained with FAHP. From the 45 enterprises where the risk assessment was applied, only 3 enterprises scored 100 full points according to the fire risk ranking method, and 30 enterprises had a score below 80 points. Out of these, 6 scored below 60 points, which is considered a low score. The distribution of enterprises within sectors was not equal. According to the results, only 6.6% of the enterprises are in compliance with legislation and standards, about 67% are inadequate in terms of fire safety and continue to operate under serious fire risks.

178. Risk Ranking System for Chemical Warfare Terrorist Agents

2003 ◽  
Author(s):  
D. Kirby ◽  
L. Hall ◽  
R. Wheaton ◽  
K. Warren
Keyword(s):  
Chemical Warfare ◽  
Ranking System ◽  
Risk Ranking

NEUTROSOPHIC SET IN INK-ALGEBRA

2020 ◽  
Vol 9 (7) ◽  
pp. 4345-4352
Author(s):  
M. Kaviyarasu ◽  
K. Indhira ◽  
V. M. Chandrasekaran
Keyword(s):  
Neutrosophic Set

scholarly journals A Neutrosophic Forecasting Model for Time Series Based on First-Order State and Information Entropy of High-Order Fluctuation

Entropy ◽  
2019 ◽  
Vol 21 (5) ◽  
pp. 455 ◽  
Author(s):  
Hongjun Guan ◽  
Zongli Dai ◽  
Shuang Guan ◽  
Aiwu Zhao
Keyword(s):  
Time Series ◽  
Information Entropy ◽  
Stock Exchange ◽  
Time Series Forecasting ◽  
High Order ◽  
Stock Index ◽  
Neutrosophic Set ◽  
Forecasting Model ◽  
Forecasting Models ◽  
Proposed Model

In time series forecasting, information presentation directly affects prediction efficiency. Most existing time series forecasting models follow logical rules according to the relationships between neighboring states, without considering the inconsistency of fluctuations for a related period. In this paper, we propose a new perspective to study the problem of prediction, in which inconsistency is quantified and regarded as a key characteristic of prediction rules. First, a time series is converted to a fluctuation time series by comparing each of the current data with corresponding previous data. Then, the upward trend of each of fluctuation data is mapped to the truth-membership of a neutrosophic set, while a falsity-membership is used for the downward trend. Information entropy of high-order fluctuation time series is introduced to describe the inconsistency of historical fluctuations and is mapped to the indeterminacy-membership of the neutrosophic set. Finally, an existing similarity measurement method for the neutrosophic set is introduced to find similar states during the forecasting stage. Then, a weighted arithmetic averaging (WAA) aggregation operator is introduced to obtain the forecasting result according to the corresponding similarity. Compared to existing forecasting models, the neutrosophic forecasting model based on information entropy (NFM-IE) can represent both fluctuation trend and fluctuation consistency information. In order to test its performance, we used the proposed model to forecast some realistic time series, such as the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX), the Shanghai Stock Exchange Composite Index (SHSECI), and the Hang Seng Index (HSI). The experimental results show that the proposed model can stably predict for different datasets. Simultaneously, comparing the prediction error to other approaches proves that the model has outstanding prediction accuracy and universality.

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