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Artificial Neural Networks

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Application of Soft Computing and Intelligent Methods in Geophysics

Part of the book series: Springer Geophysics ((SPRINGERGEOPHYS))

Abstract

Artificial neural networks are perhaps the most common method amongst intelligent methods in geophysics and are becoming increasingly popular. Because they are universal approximations, these tools can approximate any continuous function with any arbitrary precision.

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Notes

  1. 1.

    The function f(x) = A(x4 − 3x2); A > 0; is the Mexican Hat function. It has the appearance of a Mexican Hat, hence its name. It is symmetric with respect to the y-axis. Its two minima produce two stable points when viewed as a potential function in physics and engineering.

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Authors and Affiliations

  1. Department of Physics, Najafabad Branch, Islamic Azad University, Najafabad, Iran

    Alireza Hajian

  2. Applied & Environmental Geophysics Research Group, School of Physical and Geographical Sciences, Keele University, Keele, UK

    Peter Styles

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  1. Alireza Hajian
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  2. Peter Styles
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Correspondence to Alireza Hajian .

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Hajian, A., Styles, P. (2018). Artificial Neural Networks. In: Application of Soft Computing and Intelligent Methods in Geophysics. Springer Geophysics. Springer, Cham. https://doi.org/10.1007/978-3-319-66532-0_1

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