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- W3165925361 abstract "The article investigates the influence of artificial neural network’s structure on the results, with example of multlayer perceptron for forecasting some of the financial indicators. Multiple tests were made with various networks structures: different numbers of hidden layers and different numbers of neurons in these layers. Based on tests results, the increase of network’s size is effective to a certain extent, but at some point the further size increase is unreasonable. Also, the test results demonstrate that overfitting problem for multilayer perceptron is not as crucial as for the other machine learning models, such as regression. Key words: artificial neural networks, forecasting, multlayer perceptron, overfitting, artificial neural netwok’s size." @default.
- W3165925361 created "2021-06-22" @default.
- W3165925361 creator A5086888734 @default.
- W3165925361 date "2021-06-01" @default.
- W3165925361 modified "2023-10-18" @default.
- W3165925361 title "THE IMPACT OF ARTIFICIAL NEURAL NETWORK’S STRUCTURE ON ITS EFFICIENCY FOR FINANCIAL INDICATORS FORECASTING" @default.
- W3165925361 doi "https://doi.org/10.31799/2077-5687-2021-2-44-51" @default.
- W3165925361 hasPublicationYear "2021" @default.
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