HeartHealth: An Intelligent Model for Multi-Attribute Based Heart Condition Monitoring using Fuzzy-TOPSIS Method

Author(s):  
Amiya Karmakar ◽  
Kaustabh Ganguly ◽  
Partha Sarathi Banerjee
2020 ◽  
Vol 28 (46) ◽  
pp. 103-128
Author(s):  
esmaeil gharanjik ◽  
mohamad ziaadini ◽  
mostsfa hadavi nezhad ◽  
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2021 ◽  
pp. 163-174
Author(s):  
Mehdi Ghazanfari ◽  
Morteza Hashempour

Due to the important environmental effects on human life and the conflict between the mining process and environmental factors, the enactment of protectionist environmental laws in the mineral industry has received extensive attention especially in countries with high mining potential. In this regard, using an extended fuzzy TOPSIS method, this study develops a novel conceptual framework to identify the key protection laws in Iran by considering the mineral successful laws and regulations in mineral-developed countries such as Australia, Chile, India, Turkey, Canada, South Africa, and China. This helps to apply the experiences of the abovementioned countries in resolving similar conflicts in Iran’s mineral industry. The key protection laws are selected based on their national and international environmental treaties, mines’ environmental protection laws, conflict solution methods, social responsibilities in mining activity, and laws for the abandoned mines. The proposed framework demonstrates that Iran’s mineral laws require revision and more transparency to avoid ambiguity and conflict with mineral property laws and governmental rights.


2020 ◽  
Vol 5 (1) ◽  
pp. 461-474 ◽  
Author(s):  
Naiyer Mohammadi Lanbaran ◽  
Ercan Celik ◽  
Muhammed Yiğider

AbstractThe purpose of this study is extended the TOPSIS method based on interval-valued fuzzy set in decision analysis. After the introduction of TOPSIS method by Hwang and Yoon in 1981, this method has been extensively used in decision-making, rankings also in optimal choice. Due to this fact that uncertainty in decision-making and linguistic variables has been caused to develop some new approaches based on fuzzy-logic theory. Indeed, it is difficult to achieve the numerical measures of the relative importance of attributes and the effects of alternatives on the attributes in some cases. In this paper to reduce the estimation error due to any uncertainty, a method has been developed based on interval-valued fuzzy set. In the suggested TOPSIS method, we use Shannon entropy for weighting the criteria and apply the Euclid distance to calculate the separation measures of each alternative from the positive and negative ideal solutions to determine the relative closeness coefficients. According to the values of the closeness coefficients, the alternatives can be ranked and the most desirable one(s) can be selected in the decision-making process.


2019 ◽  
Vol 1 (1) ◽  
pp. 18-25
Author(s):  
Joanna Tabor

AbstractOccupational health and safety (OHS) management is a cycle of decision-making processes, many of which are in fact multi-criterion processes in nature. Therefore, it is important to look for and develop tools to support decision-makers in their actions aimed at improving work safety levels. The objective of this paper is to propose and verify the fuzzy TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method applied to compare and assess the ways OHS management systems function in different companies. The fuzzy TOPSIS method has already been used for a number of years in assessments of alternative solutions in many different areas, but the application that uses ordered fuzzy numbers is quite original in nature. It is especially beneficial to use the fuzzy approach in OHS management systems, as it makes it possible for experts to assess different criteria using most frequently used linguistic variables. The adopted approach was verified in the study of OHS management systems in four furniture manufacturing companies. Assessment criteria were requirements of the PN-N 18001: 2004 Standard. Thanks to the ordered fuzzy TOPSIS method, the analysed OHS management systems were streamlined from the point of view of 24 assessment criteria, and the best and the worst functioning system was identified. The approach presented here may constitute a significant tool for improving OHS management systems.


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