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On Uncertainty Analysis Using Random Sets in Science and Engineering

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Innovative Management in Information and Production

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Abstract

In information management systems in particular, and in science and engineering in general, uncertainty is a norm rather than an exception. Uncertainty can take on various different forms, ranging from randomness to imprecision modeled by probabilities and fuzzy sets, respectively. In view of current interests in using the so-called theory of belief functions in engineering applications, we address here a general unified framework for analyzing uncertainties. The building block of our approach is the concept of random sets.

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Author information

Authors and Affiliations

  1. New Mexico State University, Las Cruces, NM, 88003, USA

    Hung T. Nguyen

  2. Chiang Mai University, Chiang Mai, Thailand

    Hung T. Nguyen

Authors
  1. Hung T. Nguyen
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Corresponding author

Correspondence to Hung T. Nguyen .

Editor information

Editors and Affiliations

  1. Waseda University, Hibikino, Wakamatsu-ku, Kitakyushu-City 2-7, Fukuoka, 808-0135, Japan

    Junzo Watada

  2. Research Institute of Quantitative Econo, Zhejiang Gongshang University, Jiaogong Road, Hangzhou 149, Zhejiang Province, 310012, China, People's Republic

    Bing Xu

  3. , Dept. of Mathematical Sciences, National Chengchi University, ZhiNan Rd. 64Sec.2, Taipei City, 11605, Taiwan R.O.C.

    Berlin Wu

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Nguyen, H.T. (2014). On Uncertainty Analysis Using Random Sets in Science and Engineering. In: Watada, J., Xu, B., Wu, B. (eds) Innovative Management in Information and Production. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-4857-0_1

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  • DOI: https://doi.org/10.1007/978-1-4614-4857-0_1

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-4856-3

  • Online ISBN: 978-1-4614-4857-0

  • eBook Packages: EngineeringEngineering (R0)

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