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Introduction

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Book cover Applications of Soft Computing in Time Series Forecasting

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 330))

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Abstract

As the application of information technology is growing very rapidly, data in various formats have also proliferated over the time.

The best way to predict your future is to create it.

Peter F. Drucker

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Notes

  1. 1.

    References are: (Singh and Borah 2012, 2013a, b, c).

  2. 2.

    References are: (Chen 1996; Huarng 2001a; Hwang et al 1998; Song and Chissom 1993a, 1994).

  3. 3.

    References are: (Chen 1996; Huarng 2001b; Huarng et al 2007; Hwang et al 1998).

  4. 4.

    References are: (Chen 1996; Cheng et al 2006; Hwang et al 1998; Song and Chissom 1993a, b, 1994).

  5. 5.

    References are: (Song and Chissom 1993a, b, 1994).

  6. 6.

    References are:(Egrioglu et al 2011; Huarng 2001b; Huarng and Yu 2006; Li and Chen 2004).

  7. 7.

    References are: (Huang et al 2011; Kuo et al 2009, 2010; Park et al 2010; Sheikhan and Mohammadi 2012).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Thapar University, Patiala, India

    Pritpal Singh

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  1. Pritpal Singh
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Singh, P. (2016). Introduction. In: Applications of Soft Computing in Time Series Forecasting. Studies in Fuzziness and Soft Computing, vol 330. Springer, Cham. https://doi.org/10.1007/978-3-319-26293-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-26293-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26292-5

  • Online ISBN: 978-3-319-26293-2

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