Prediction of cotton yield in Kenya

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DC Field	Value	Language
dc.contributor.author	Mwasiagi, Josphat Igadwa	-
dc.date.accessioned	2021-07-21T09:54:54Z	-
dc.date.available	2021-07-21T09:54:54Z	-
dc.date.issued	2008-08	-
dc.identifier.uri	http://ir.mu.ac.ke:8080/jspui/handle/123456789/4877	-
dc.description.abstract	COTTON YIELD IS ONE OF THE INDICATORS for describing agricultural efficiency from different resource management methods in the cotton-growing industry. Selected cotton-growing cost factors were used to design an artificial neural network model to predict cotton yield in Kenya. This neural network model was able to predict cotton yield with a satisfactory performance error of 0.204 kg/ha and a regression correlation coefficient between network output and actual yield of 0.94	en_US
dc.language.iso	en	en_US
dc.publisher	South Africa Journal of Science	en_US
dc.subject	Cotton	en_US
dc.title	Prediction of cotton yield in Kenya	en_US
dc.type	Article	en_US
Appears in Collections:	School of Engineering

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