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Neural Network Application to Support Regression Model in Forecasting Single-Sectional Demand for Telecommunications Services

Author

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  • Kaczmarczyk Paweł

    (The State University of Applied Sciences in Płock, Faculty of Economics and Information Technology, Department of Economics, Gałczyńskiego 28, 09-400 Płock, Poland)

Abstract

The aim of this research study is to test the effectiveness of the single-sectional integrated model, in which a neural network is applied to support a regression, as a consistent tool for short-term forecasting of hourly demand (in sec.) for telecommunications services. The theoretical part of the paper involves the idea of the single-sectional integrated model and differences between this model and a multi-sectional integrated model. Moreover, the research methodology is described, i.e. the elements used in the constructed model (the feedforward neural model and the regression with dichotomous explanatory variables), and the manner of their integration are discussed.

Suggested Citation

  • Kaczmarczyk Paweł, 2018. "Neural Network Application to Support Regression Model in Forecasting Single-Sectional Demand for Telecommunications Services," Folia Oeconomica Stetinensia, Sciendo, vol. 18(2), pages 159-177, December.
    • Handle: RePEc:vrs:foeste:v:18:y:2018:i:2:p:159-177:n:11
    DOI: 10.2478/foli-2018-0025
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    References listed on IDEAS

    as
    1. Kaczmarczyk Paweł, 2016. "Integrated Model of Demand for Telephone Services in Terms of Microeconometrics," Folia Oeconomica Stetinensia, Sciendo, vol. 16(2), pages 72-83, December.
    2. Pawel Kaczmarczyk, 2017. "Microeconometric Analysis of Telecommunication Services Market with the Use of SARIMA Models," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 17, pages 41-57.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Prediction System; linear regression; feedforward neural network; forecasting;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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