University of Khartoum

Prediction of Blue Nile Soil Profile in Khartoum State Using Artificial Neural Network

Prediction of Blue Nile Soil Profile in Khartoum State Using Artificial Neural Network

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dc.contributor.advisor Dr. EL Hussein ELarabi en_US
dc.contributor.author El Hassan, Mutwakil Ali M.
dc.date.accessioned 2015-05-14T12:10:44Z
dc.date.available 2015-05-14T12:10:44Z
dc.date.issued 2015-05-14
dc.date.submitted 2009-04
dc.identifier.uri http://khartoumspace.uofk.edu/handle/123456789/10839
dc.description 1131page
dc.description.abstract This thesis deals with the potential application of neural network technology to build up and to investigate a powerful network capable to classify and predict some soil properties at the blue Nile area in Khartoum state based on previous investigated site conditions, Also the effect of Artificial neural network ANN geometry and some internal parameters (learning rate and momentum) on the performance of ANN models is studied. A large database (data of 55 sites) of actual available site investigation data is used to develop and verify the ANN model. About 38% of the total database (21 sites) is used as input data to construct seventeen ANN models using Neuroshell2 program. A data of new34 sites were predicted by the models. The results indicate the neural network is a useful technique and have an ability to make relationships between the input parameters (the three dimensional coordinates) and the output parameters (soil classification and its l properties) with an acceptable degree of accuracy. en_US
dc.language.iso en en_US
dc.publisher UOFK en_US
dc.subject Blue Nile Soil Profile,Khartoum State,Artificial Neural Network en_US
dc.title Prediction of Blue Nile Soil Profile in Khartoum State Using Artificial Neural Network en_US
dc.type Thesis en_US
dc.Degree M.Sc en_US
dc.Faculty Building & Road Research Institute en_US
dc.contributor.faculty Building Technology en_US

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