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CLASSIFICATION OF SOIL TYPE USING BACKPROPAGATION NEURAL NETWORK

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dc.contributor.author Htun, Wanna
dc.contributor.author Htay, Sandar
dc.date.accessioned 2019-07-23T02:46:01Z
dc.date.available 2019-07-23T02:46:01Z
dc.date.issued 2010-12-16
dc.identifier.uri http://onlineresource.ucsy.edu.mm/handle/123456789/1195
dc.description.abstract A number of classification systems have been developed depending on the intended purpose of the system. Soil classification has proved to be very useful for soil engineers. Classification of soil type is an ever challenging area of investigation for scientists. This system is used to classify soil according to their general behavior under given physical conditions. The system is present soil classification using Backpropagation Neural Network. The result is very encouraging and it is found that the feature based soil type can make prediction with degree of accuracy. Classification of soil type can also build an awareness and knowledge of each irrigated field. en_US
dc.language.iso en en_US
dc.title CLASSIFICATION OF SOIL TYPE USING BACKPROPAGATION NEURAL NETWORK en_US
dc.type Article en_US


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