Suscripción a Biblioteca: Guest
Portal Digitalde Biblioteca Digital eLibros Revistas Referencias y Libros de Ponencias Colecciones
International Journal for Uncertainty Quantification
Factor de Impacto: 4.911 Factor de Impacto de 5 años: 3.179 SJR: 1.008 SNIP: 0.983 CiteScore™: 5.2

ISSN Imprimir: 2152-5080
ISSN En Línea: 2152-5099

Acceso abierto

International Journal for Uncertainty Quantification

DOI: 10.1615/Int.J.UncertaintyQuantification.v2.i1.60
pages 73-94

ON THE ROLE OF DATA MINING TECHNIQUES IN UNCERTAINTY QUANTIFICATION

Chandrika Kamath
Lawrence Livermore National Laboratory, 7000 East Avenue, Livermore, California, 94551, USA

SINOPSIS

Techniques from scientific data mining are increasingly being used to analyze and understand data from scientific observations, simulations, and experiments. These methods provide scientists the opportunity to automate the tedious manual processing of the data, control complex systems, and gain insights into the phenomenon being modeled or observed. This process of data-driven scientific inference borrows ideas and solutions from a range of fields including machine learning, image and video processing, statistics, high-performance computing, and pattern recognition. The tasks involved in these analyses include the extraction of structures from the data, the identification of representative features for these structures, dimension reduction, and building predictive and descriptive models. At first glance, data mining and data-driven analysis may appear unrelated to stochastic modeling and uncertainty quantification. But, as we show in this paper, there are commonalities in the problems addressed and techniques used, providing the two communities the opportunity to benefit from the expertise and experiences of each other.


Articles with similar content:

LEARNING TOGETHER OR GOING IT ALONE: HOW COMMUNITY CONTEXTS SHAPE THE IDENTITY DEVELOPMENT OF MINORITY WOMEN IN COMPUTING
Journal of Women and Minorities in Science and Engineering, Vol.19, 2013, issue 4
A. Susan Jurow, Sarah Hug
UNDERGRADUATE STEM LEADERSHIP: UNDERSTANDING THE GENDER GAP IN SELF-RATED LEADERSHIP ABILITY BY EXPLORING WOMEN'S MEANING-MAKING
Journal of Women and Minorities in Science and Engineering, Vol.26, 2020, issue 2
Jennifer Blaney
PLUG AND PLAY FRAMEWORK FOR COMBINATORAL PROBLEM HEURISTICS
Flexible Automation and Intelligent Manufacturing, 1997:
Proceedings of the Seventh International FAIM Conference, Vol.0, 1997, issue
Andrew Wooster
A CASE FOR USING SWIVL FOR DIGITAL OBSERVATION IN AN ONLINE OR BLENDED LEARNING ENVIRONMENT
International Journal on Innovations in Online Education, Vol.2, 2018, issue 2
Mary Kelly, Selina McCoy, Aoife Lynam
STUDENT USE OF SCAFFOLDING RESOURCES IN A HYBRID COURSE: EVIDENCE FROM EYE-TRACKING
International Journal on Innovations in Online Education, Vol.4, 2020, issue 1
Aliye Karabulut-Ilgu, Anna Slavina, Charles Jahren