Trust prediction using Z-numbers and Artificial Neural Networks

Publication Type:
Conference Proceeding
Citation:
IEEE International Conference on Fuzzy Systems, 2014, pp. 522 - 528
Issue Date:
2014-01-01
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© 2014 IEEE. Trust modeling of both the interacting parties in a virtual world, is a critical element of business intelligence. A key aspect in trust modeling is to be able to accurately predict the future trust value of an interacting party. In this paper, we propose an intelligent method for predicting the future trust value of a trusted entity. We propose the use of Z-number to represent both the trust value and its corresponding reliability. Subsequently, we apply Artificial Neural Network (ANN) to predict future trust values. We generate a large number of synthetic time series, with a view to model real-world trust values of trusted entity. We validate the working of our methodology using the generated time series.
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