Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/42230
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dc.contributor.authorRajakumar, C.-
dc.contributor.authorMeenambal, T.-
dc.date.accessioned2017-06-14T05:01:22Z-
dc.date.available2017-06-14T05:01:22Z-
dc.date.issued2017-07-
dc.identifier.issn0975-1033 (Online); 0379-5136 (Print)-
dc.identifier.urihttp://nopr.niscair.res.in/handle/123456789/42230-
dc.description1454-1461en_US
dc.description.abstractFor analysis of stabilization of soil using fly ash, MAT LAB (7.12.0) has been employed. The effects of number of neurons in hidden layer with different algorithms are also investigated. Levenberg-Marquardt back propagation shows maximum R value of 0.97637 and minimum MSE value of 8.0242e-11. Economic beneficial are also investigated with local rates of the materials.en_US
dc.language.isoen_USen_US
dc.publisherNISCAIR-CSIR, Indiaen_US
dc.rights CC Attribution-Noncommercial-No Derivative Works 2.5 Indiaen_US
dc.sourceIJMS Vol.46(07) [July 2017]en_US
dc.subjectSubgradeen_US
dc.subjectFlyashen_US
dc.subjectGeotextileen_US
dc.subjectCBRen_US
dc.subjectANNen_US
dc.subjectMRAen_US
dc.subjectCost analysisen_US
dc.titleArtificial neural network modelling and economic analysis of soil subgrade stabilized with flyash and geotextileen_US
dc.typeArticleen_US
Appears in Collections:IJMS Vol.46(07) [July 2017]

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