Author

  • Wittaya Pornpatcharapong

    • School of Management, Shinawatra University, Bangkok, Thailand
    • Thailand

  • Pacapol Jakrapan Anurit

    • School of Management, Shinawatra University, Bangkok, Thailand
    • Thailand

  • Chuvej Chansa-ngavej

    • School of Management, Shinawatra University, Bangkok, Thailand
    • Thailand

  • Supachok Wiriyacosol

    • School of Management, Shinawatra University, Bangkok, Thailand
    • Thailand

  • Chanchai Bunchapattanasakda

    • School of Management, Shinawatra University, Bangkok, Thailand
    • Thailand

Abstract

This paper aims to prioritize impact factors which affect Thai rural village development. The basic village-leveled information database (NRD-2C) of the Community Development Department (CDD), Ministry of Interior, Thailand, was applied with Artificial Neural Networks (ANN) to measure the amount of impact for each factor affecting Thai rural village development. According to results, the top 5 impact factors are “Land Possession”, “Electricity”, “Communication”, “Educational Level”, and “Household Industry” with 17.88, 15.35, 14.02, 12.06, and 10.57 score of impact respectively with 95.60 percent of estimated accuracy.

Keywords

References

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How to Cite

Pornpatcharapong, W., Anurit, P. J., Chansa-ngavej, C., Wiriyacosol, S., & Bunchapattanasakda, C. (2011). The Use of Artificial Neural Networks to Prioritize Impact Factors Affecting Thai Rural Village Development. Journal of Social and Development Sciences, 2(2), 89-93. https://doi.org/10.22610/jsds.v2i2.657

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Copyright (c) 2011 Wittaya Pornpatcharapong, Pacapol Jakrapan Anurit, Chuvej Chansa-ngavej, Supachok Wiriyacosol, Chanchai Bunchapattanasakda (Author)

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Section

Research Paper

Published in

Vol. 2 No. 2 (2011) Learning, Oil Economies & Rural Development View issue contents

Published

2011-08-15

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