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Neural Networks Based Forecasting for Romanian Clothing Sector

In: Intelligent Fashion Forecasting Systems: Models and Applications

Author

Listed:
  • Logica Banica

    (University of Pitesti)

  • Daniela Pirvu

    (University of Pitesti)

  • Alina Hagiu

    (University of Pitesti)

Abstract

Clothing industry enjoys a high level of attention on all world markets, despite the prolonged economic crisis. Companies have turned to knowledge and research, processing and analyzing information obtained from the market analysis, surveys, their own and their competitor’s sales evolution, and are making use of short- and medium-term forecasts as powerful tools for the top management. The paper presents a twofold approach regarding forecasting of the financial indicators and trends related to the Romanian clothing industry, firstly at macroeconomic level, taking into account the interest of potential investors in this field, and secondly at microeconomic level, representing the analysis of the results for an operational company.

Suggested Citation

  • Logica Banica & Daniela Pirvu & Alina Hagiu, 2014. "Neural Networks Based Forecasting for Romanian Clothing Sector," Springer Books, in: Tsan-Ming Choi & Chi-Leung Hui & Yong Yu (ed.), Intelligent Fashion Forecasting Systems: Models and Applications, edition 127, chapter 0, pages 161-194, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-39869-8_9
    DOI: 10.1007/978-3-642-39869-8_9
    as

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