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Artificial Intelligence and Computational Science

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Computational Sciences and Artificial Intelligence in Industry

Part of the book series: Intelligent Systems, Control and Automation: Science and Engineering ((ISCA,volume 76))

Abstract

In this note, we discuss the interaction between two ways of scientific analysis. The first (classical) way is known as Mathematical Modeling (MM). It is based on a model created by humans and presented in mathematical terms. Scientific Computing (SC) is an important tool of MM developed to quantitatively analyze the model. Artificial Intelligence (AI) forms a new way of scientific analysis. AI systems arise as a result of a different process. Here, we take a sequence of correct input–output data, perform Machine Learning (ML), and get a model (hidden in a network). In this process, computational methods are used to create a network type model. We briefly discuss special methods used for this purpose (such as evolutionary algorithms), give a concise overview of results related to applications of AI in computer simulation of real-life problems, and discuss several open problems.

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Author information

Authors and Affiliations

  1. Faculty of Information Technology, University of Jyväskylä, 35, FI-40014, Jyväskylä, Finland

    Pekka Neittaanmäki & Sergey Repin

Authors
  1. Pekka Neittaanmäki
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  2. Sergey Repin
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Corresponding author

Correspondence to Pekka Neittaanmäki .

Editor information

Editors and Affiliations

  1. Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland

    Tero Tuovinen

  2. CIMNE, International Center for Numerical Methods in Engineering, Barcelona, Spain

    Jacques Periaux

  3. Faculty of Information Technology, University of Jyväskylä, Jyväskylä, Finland

    Pekka Neittaanmäki

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Neittaanmäki, P., Repin, S. (2022). Artificial Intelligence and Computational Science. In: Tuovinen, T., Periaux, J., Neittaanmäki, P. (eds) Computational Sciences and Artificial Intelligence in Industry. Intelligent Systems, Control and Automation: Science and Engineering, vol 76. Springer, Cham. https://doi.org/10.1007/978-3-030-70787-3_3

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