Abstract
A heuristic method (computation of weighted averages) is considered for risk analysis. It is improved upon by utilizing the Perceptron Learning Theorem and Quadratic Programming. Experimental work shows that both techniques give good results, the former one being somewhat more efficient in terms of CPU-time used. In spite of certain theoretical shortcomings it is argued that the familiar paradigm offers considerable potential for practical applications.
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© 1999 Springer-Verlag Berlin Heidelberg
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Falkowski, BJ. (1999). Risk Analysis Using Perceptrons and Quadratic Programming. In: Reusch, B. (eds) Computational Intelligence. Fuzzy Days 1999. Lecture Notes in Computer Science, vol 1625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48774-3_59
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DOI: https://doi.org/10.1007/3-540-48774-3_59
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66050-7
Online ISBN: 978-3-540-48774-6
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