A3 Book section, Chapters in research books
Artificial Intelligence and Computational Science (2022)


Neittaanmäki, P., & Repin, S. (2022). Artificial Intelligence and Computational Science. In T. T. Tuovinen, J. Periaux, & P. Neittaanmäki (Eds.), Computational Sciences and Artificial Intelligence in Industry : New Digital Technologies for Solving Future Societal and Economical Challenges (pp. 27-35). Springer. Intelligent Systems, Control and Automation: Science and Engineering, 76. https://doi.org/10.1007/978-3-030-70787-3_3


JYU authors or editors


Publication details

All authors or editors: Neittaanmäki, Pekka; Repin, Sergey

Parent publication: Computational Sciences and Artificial Intelligence in Industry : New Digital Technologies for Solving Future Societal and Economical Challenges

Parent publication editors: Tuovinen, Tero T.; Periaux, Jacques; Neittaanmäki, Pekka

ISBN: 978-3-030-70786-6

eISBN: 978-3-030-70787-3

Journal or series: Intelligent Systems, Control and Automation: Science and Engineering

ISSN: 2213-8986

eISSN: 2213-8994

Publication year: 2022

Number in series: 76

Pages range: 27-35

Number of pages in the book: 275

Publisher: Springer

Place of Publication: Cham

Publication country: Switzerland

Publication language: English

DOI: https://doi.org/10.1007/978-3-030-70787-3_3

Publication open access: Not open

Publication channel open access:

Additional information: The CSAI 2019 Conference (Computational Science and AI in Industry: New Digital Technologies for Solving Future Societal and Economical Challenges) took place at Jyväskylä, Finland, on June 12–14, 2019.


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.


Keywords: mathematical models; simulation; computational science; machine learning; artificial intelligence; evolutionary computation

Free keywords: scientific computations; machine learning; Artificial intelligence; evolutionary algorithms


Contributing organizations


Ministry reporting: Yes

Preliminary JUFO rating: 2


Last updated on 2021-26-08 at 09:39