Classifying behavioural traits of small-scale farmers: Use of a novel artificial neural network (ANN) classifier

dc.contributor.authorJena, P.R.
dc.contributor.authorMajhi, R.
dc.date.accessioned2026-02-06T06:39:01Z
dc.date.issued2016
dc.description.abstractThis 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.
dc.identifier.citationInternational Conference on Electrical, Electronics, and Optimization Techniques, ICEEOT 2016, 2016, Vol., , p. 4164-4169
dc.identifier.urihttps://doi.org/10.1109/ICEEOT.2016.7755501
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/32014
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectArtificial neural network (ANN)
dc.subjectclassification
dc.subjectfarmer behaviour
dc.subjectfood security
dc.titleClassifying behavioural traits of small-scale farmers: Use of a novel artificial neural network (ANN) classifier

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