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RETRACTED ARTICLE: Determination of the most influential factors for number of patents prediction by adaptive neuro-fuzzy technique

Author

Listed:
  • Miloš Milovančević

    (University of Niš)

  • Dušan Marković

    (University of Niš)

  • Vlastimir Nikolić

    (University of Niš)

  • Igor Mladenović

    (University of Niš)

Abstract

Number of patents may be developed on the basis on different natural and science and technological factors. Number of patents prediction based on the different factors in many countries is analyzed in this investigation. These factors represent natural and science resources. The method of ANFIS (adaptive neuro fuzzy inference system) was applied to the data in order to select the most influential factors for the number of patents prediction. Five inputs are considered: research and development (R&D) resources, natural resources, quality of academic institutions, quality of collaboration with the private sector and quality of education. As the ANFIS output, number of patents is considered. The ANFIS process for variable selection is also implemented in order to detect the predominant factors affecting the prediction of number of patents. Results show that the R&D is the most influential factor for the number of patents prediction.

Suggested Citation

  • Miloš Milovančević & Dušan Marković & Vlastimir Nikolić & Igor Mladenović, 2017. "RETRACTED ARTICLE: Determination of the most influential factors for number of patents prediction by adaptive neuro-fuzzy technique," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1207-1216, May.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:3:d:10.1007_s11135-016-0326-1
    DOI: 10.1007/s11135-016-0326-1
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    References listed on IDEAS

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    Cited by:

    1. Pieter E. Stek, 2020. "Mapping high R&D city-regions worldwide: a patent heat map approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(1), pages 279-296, February.

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