IDEAS home Printed from https://ideas.repec.org/p/can/series/2005-02.html
   My bibliography  Save this paper

Predicción mediante algoritmos genéticos con matriz de transición. Una aplicación a la demanda turística de Tenerife

Author

Listed:
  • Montserrat Hernández López

    (Dpto. de Economía de las Instituciones, Estadística Económica y Econometría Facultad de Ciencias Económicas y Empresariales; Universidad de La Laguna Campus de Guajara.38071 La Laguna; 38071; La Laguna; Tenerife.Islas Canarias.España Teléfono: 922317032)

Abstract

Aunque los algoritmos genéticos se diseñaron originalmente como método de optimización, también pueden ser utilizados, en el contexto económico, como herramienta predictiva de los cambios en la composición de una población, en términos de las características individuales de los agentes que la componen. En este documento, se desarrolla un algoritmo genético específico capaz de predecir los cambios en las características de los turistas que visitan el sur de Tenerife. Los resultados obtenidos sugieren la conveniencia de sustituir los tradicionales operadores de cruce y mutación por la acción de una adecuada matriz de transición. Esta matriz dirige la dinámica de transformación de la población en el sentido de que permite introducir consideraciones económicas que otorgan mayores probabilidades a ciertas transformaciones en las características de los turistas que visitan la Isla.

Suggested Citation

  • Montserrat Hernández López, 2005. "Predicción mediante algoritmos genéticos con matriz de transición. Una aplicación a la demanda turística de Tenerife," Documentos de trabajo conjunto ULL-ULPGC 2005-02, Facultad de Ciencias Económicas de la ULPGC.
  • Handle: RePEc:can:series:2005-02
    as

    Download full text from publisher

    File URL: http://www.bibliotecas.ulpgc.es/fcee/hemeroteca/documentos%20de%20trabajo/DocumentosDTrabajo/doc51/DT2005-02.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Venkatesan, Rajkumar & Kumar, V., 2002. "A genetic algorithms approach to growth phase forecasting of wireless subscribers," International Journal of Forecasting, Elsevier, vol. 18(4), pages 625-646.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Peters, Kay & Albers, Sönke & Kumar, V., 2008. "Is there more to international Diffusion than Culture? An investigation on the Role of Marketing and Industry Variables," EconStor Preprints 27678, ZBW - Leibniz Information Centre for Economics.
    2. Chang-Gyu Yang & Silvana Trimi & Sang-Gun Lee & Joon-Sun Yang, 2017. "A Survival Analysis of Business Insolvency in ICT and Automobile Industries," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(06), pages 1523-1548, November.
    3. Edward Oughton, 2018. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04 (revised), Cambridge Judge Business School, University of Cambridge.
    4. Shagun Srivastava & Madhvendra Misra, 2014. "Developing Evaluation Matrix for Critical Success Factors in Technology Forecasting," Global Business Review, International Management Institute, vol. 15(2), pages 363-380, June.
    5. Christos Michalakelis & Georgia Dede & Dimitris Varoutas & Thomas Sphicopoulos, 2010. "Estimating diffusion and price elasticity with application to telecommunications," Netnomics, Springer, vol. 11(3), pages 221-242, October.
    6. Edward Oughton, 2017. "Towards 5G: scenario-based assessment of the future supply and demand for mobile telecommunications infrastructure," Working Papers 2017/04, Cambridge Judge Business School, University of Cambridge.
    7. Bartoš, Erik & Pinčák, Richard, 2017. "Identification of market trends with string and D2-brane maps," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 57-70.
    8. Mukisa, Nicholas & Zamora, Ramon & Lie, Tek Tjing, 2021. "Diffusion forecast for grid-tied rooftop solar photovoltaic technology under store-on grid scheme model in Sub-Saharan Africa: Government role assessment," Renewable Energy, Elsevier, vol. 180(C), pages 516-535.
    9. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
    10. Goodwin, Paul & Meeran, Sheik & Dyussekeneva, Karima, 2014. "The challenges of pre-launch forecasting of adoption time series for new durable products," International Journal of Forecasting, Elsevier, vol. 30(4), pages 1082-1097.
    11. Meade, Nigel & Islam, Towhidul, 2006. "Modelling and forecasting the diffusion of innovation - A 25-year review," International Journal of Forecasting, Elsevier, vol. 22(3), pages 519-545.
    12. Michalakelis, C. & Sphicopoulos, T., 2012. "A population dependent diffusion model with a stochastic extension," International Journal of Forecasting, Elsevier, vol. 28(3), pages 587-606.
    13. de Menezes, Lilian M. & Nikolaev, Nikolay Y., 2006. "Forecasting with genetically programmed polynomial neural networks," International Journal of Forecasting, Elsevier, vol. 22(2), pages 249-265.

    More about this item

    Keywords

    Algoritmos genéticos; predicción económica; operadores genéticos; matriz de transición.;
    All these keywords.

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:can:series:2005-02. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Patricia Santana (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.