Please use this identifier to cite or link to this item: https://idr.l1.nitk.ac.in/jspui/handle/123456789/7964
Title: Classifying behavioural traits of small-scale farmers: Use of a novel artificial neural network (ANN) classifier
Authors: Jena, P.R.
Majhi, R.
Issue Date: 2016
Citation: International Conference on Electrical, Electronics, and Optimization Techniques, ICEEOT 2016, 2016, Vol., , pp.4164-4169
Abstract: This paper develops and employs a novel artificial neural network (ANN) model to study farmers' behaviour towards decision making on maize production in Kenya. The paper has compared the accuracy level of ANN based model and the statistical model and found out that the ANN model has achieved higher accuracy and efficiency. The findings from the study reveal that the farmers are mostly influenced by their demographic and food security for decision making. Further to examine the relative importance of different demographic and food security characteristics, an ANOVA test is undertaken. The results found that education and food security indices are instrumental in influencing farmers' decision making. � 2016 IEEE.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/7964
Appears in Collections:2. Conference Papers

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.