The Use of Artificial Neural Networks to Prioritize Impact Factors Affecting Thai Rural Village Development

  • Wittaya Pornpatcharapong
  • Chuvej Chansa-ngavej .
  • Supachok Wiriyacosol .
  • Chanchai Bunchapattanasakda .
DOI: https://doi.org/10.22610/jsds.v2i2.657

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 Possessionâ€, “Electricityâ€, “Communicationâ€, “Educational Levelâ€, 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.

Downloads

Download data is not yet available.
Published
2011-08-15
How to Cite
Pornpatcharapong, W., ., C. C.- ngavej, ., S. W., & ., C. B. (2011). The Use of Artificial Neural Networks to Prioritize Impact Factors Affecting Thai Rural Village Development. Journal of Social and Development Sciences, 2(2), pp. 89-93. https://doi.org/10.22610/jsds.v2i2.657
Issue
Vol 2 No 2 (2011)
Section
Research Paper

Copyright (c) 2011 Journal of Social and Development Sciences

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Author (s) should affirm that the material has not been published previously. It has not been submitted and it is not under consideration by any other journal. At the same time author (s) need to execute a publication permission agreement to assume the responsibility of the submitted content and any omissions and errors therein. After submission of a revised paper, the editorial team edits and formats manuscripts to bring uniformity and standardization in published material.

This work will be licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) and under condition of the license, users are free to read, copy, remix, transform, redistribute, download, print, search or link to the full texts of articles and even build upon their work as long as they credit the author for the original work. Moreover, as per journal policy author (s) hold and retain copyrights without any restrictions.