EconPapers    
Economics at your fingertips  
 

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

Wittaya Pornpatcharapong, Chuvej Chansa-ngavej, Supachok Wiriyacosol and Chanchai Bunchapattanasakda

Journal of Social and Development Sciences, 2011, vol. 2, issue 2, 89-93

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.

Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://ojs.amhinternational.com/index.php/jsds/article/view/657/657 (application/pdf)
https://ojs.amhinternational.com/index.php/jsds/article/view/657 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:rnd:arjsds:v:2:y:2011:i:2:p:89-93

DOI: 10.22610/jsds.v2i2.657

Access Statistics for this article

More articles in Journal of Social and Development Sciences from AMH International
Bibliographic data for series maintained by Muhammad Tayyab ().

 
Page updated 2025-03-19
Handle: RePEc:rnd:arjsds:v:2:y:2011:i:2:p:89-93