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Using Fuzzy Logic to Increase the Accuracy of E-Commerce Risk Assessment Based on an Expert System
2017
Journal:  
Engineering, Technology & Applied Science Research
Author:  
Abstract:

Abstract Strong adaptive control can be exercised even without access to accurate data inputs. Such control is possible through fuzzy mathematics, which is a meta-collection of Boolean logic principles that imply relative accuracy. Fuzzy mathematics find applications in e-commerce, where different risk analysis methods are available for risk assessment and estimation. Such approaches can be quantitative or qualitative, depending on the type of examined data. Quantitative methods are grounded in statistics, whereas qualitative methods are based on expert judgments and fuzzy set theory. Given that qualitative methods are very subjective and deal with vague or inaccurate data, fuzzy logic can be used to extract useful information from data inaccuracies. In this study, a model based on the opinions of e-commerce security experts was designed and implemented by using fuzzy expert systems and MATLAB. A case study was conducted to validate the effectiveness of the Model.

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2017
Author:  
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Engineering, Technology & Applied Science Research

Journal Type :   Uluslararası

Metrics
Article : 1.845
Cite : 2.898
2023 Impact : 0.733
Engineering, Technology & Applied Science Research