Complex Systems and Data Science

Uzay Çetin

Yildiz Social Science Review, 2020, vol. 6, issue 2, 119-130

Abstract: Complex Systems are organic systems that can self-organize themselves and adapt to changing conditions. A complex system results from a huge amount of interactions of many agents following simple rules. It is not the agents that are essential, but the relationships between them. Deep learning models created a much greater paradigm change in solving engineering problems than the one created by complex systems in science. Deep learning models are composed of a layered structure. The first layers automatically learn the simplest features, while the next layers have the ability to extract highlevel features in a hierarchical manner form simple to more complex. Special deep learning algorithms can even capture temporal and spatial relationships. The purpose of this article is to emphasize the fact that data science, machine learning and complex systems will provide us a complementary perspective to study our universe.

Keywords: Complex Systems; Data Science; Deep Learning; Anomaly DetectionJournal: Yildiz Social Science Review (search for similar items in EconPapers)
JEL-codes: F00 F30 G00 G10 K00 K20 M00 M20 O10 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:aye:journl:v:6:y:2020:i:2:p:119-130

DOI: 10.51803/yssr.833992

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