APPLICATION OF NEURAL NETWORK TECHNOLOGIES FOR PREDICTING THE VOLUME OF CARGO TRANSPORTATION

Abstract

The article is devoted to the research of forecasting of cargo turnover on the basis of the use of the method of neural networks. The main advantages and disadvantages of using this technique are highlighted. The characteristics of the quality of various types of neural networks that have been built are presented. The principle of work and methods of constructing neural networks for solving various types of economic problems and decision-making are analysed. Recommendations for improving the accuracy of the result using the method of neural networks are given. The volume of total cargo turnover in Ukraine for 2018 is projected.

Authors and Affiliations

T. I. Oleshko, R. I. Khomenko

Keywords

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  • EP ID EP516786
  • DOI -
  • Views 109
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How To Cite

T. I. Oleshko, R. I. Khomenko (2018). APPLICATION OF NEURAL NETWORK TECHNOLOGIES FOR PREDICTING THE VOLUME OF CARGO TRANSPORTATION. Проблеми системного підходу в економіці, 2(64), -. https://europub.co.uk/articles/-A-516786