Machine learning for the self-organization of distributed systems in economic applications

Journal Title: Współczesna Gospodarka - Year 2017, Vol 8, Issue 1

Abstract

In this paper, an application of machine learning to the problem of self-organization of distributed systems has been discussed with regard to economic applications, with particular emphasis on supervised neural network learning to predict stock investments and some ratings of companies. In addition, genetic programming can play an important role in the preparation and testing of several financial information systems. For this reason, machine learning applications have been discussed because some software applications can be automatically constructed by genetic programming. To obtain a competitive advantage, machine learning can be used for the management of self-organizing cloud computing systems performing calculations for business. Also the use of selected economic self-organizing distributed systems has been described, including some testing methods of predicting borrower reliability. Finally, some conclusions and directions for further research have been proposed.

Authors and Affiliations

Jerzy Balicki, Waldemar Korłub

Keywords

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  • EP ID EP245983
  • DOI -
  • Views 96
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How To Cite

Jerzy Balicki, Waldemar Korłub (2017). Machine learning for the self-organization of distributed systems in economic applications. Współczesna Gospodarka, 8(1), 1-26. https://europub.co.uk/articles/-A-245983