Editorial of special issue on: Applications of risk analysis and analytics in engineering and economics

Author

Juan Pérez, Ángel Alejandro

Armas Adrián, Jésica de

Calvet Liñan, Laura

Serra Mochales, Isabel

Other authors

Centre de Recerca Matemàtica

Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)

Universitat Pompeu Fabra

Publication date

2018-10-16T13:13:23Z

2018-10-16T13:13:23Z

2017-11



Abstract

In areas such as engineering, economics, and insurance, real-world systems are becoming increasingly complex to analyse due to their global scale as well as to the uncertainty and dynamic conditions that characterises realistic scenarios. This increasing complexity makes risk analysis and analytic (RA&A) methods more important than ever, since being able to design, develop, and operate real-live systems while assessing and reducing their risk of malfunctions or inefficiencies constitutes one of the most relevant challenges in our current society. RA&A methods and techniques have rapidly evolved over the last years. One factor that explains this development is outstanding and continuous improvement in software and computing power, which facilitates the use of hybrid algorithms combining risk/reliability principles with modern optimisation and simulation frameworks. Another factor is the increasing use of problem solving approaches that benefit from the so-called "big data" phenomenon. However, despite these significant advances in this scientific arena, there seems to be an important gap between theory and practice; most industrial sectors (including engineering, economics, and insurance) are only starting to employ the full potential of state-of-the-art scientific advances in RA&A.

Document Type

Others
Published version

Language

English

Subjects and keywords

risk analysis and analytic methods (RA&A); hybrid algorithms; análisis del riesgo y métodos analíticos; algoritmos híbridos; anàlisi del risc i mètodes analítics; algorismes híbrids; Computer algorithms; Algorismes computacionals; Algoritmos computacionales

Publisher

International Journal of Data Analysis Techniques and Strategies

Related items

International Journal of Data Analysis Techniques and Strategies, 2017, 9(4)

http://www.inderscience.com/browse/getEditorial.php?articleID=5433

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