University of Khartoum

Prediction Of Blue Nile Profile Using Artificial Intelligence Technique

Prediction Of Blue Nile Profile Using Artificial Intelligence Technique

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Title: Prediction Of Blue Nile Profile Using Artificial Intelligence Technique
Author: Elarabi, Hussien; Ali, Mutwakil
Abstract: Artificial NeuraL Networks (ANNs) Are computational models broadly inspired by the organization of the human brain. The Most important features of aneural network are its abilities to learn, to process and to make models for all input data, to produce an output with error tolerant according to the error of supplied input. In This study, ANNs Are used for classification and of soil propertieat different depths in Khartoum Blue Nile area. This Study used 38 % Of the available sites investigation data (data Of 21 sites) as input data to predict the rest data (data Of 34 sites), about 62 % Of total collected data. Seventeen Models of Neural Networks are constructed and developed to predict soil layers and to estimate some soil parameters in specified locations in Khartoum Blue Nile area, the results indicate Neural Networks is a useful technique to make relationships between the input parameters of the three dimensional coordinates and the outputs of soil classification prediction and some soil parameter in specified studied area. this paper shows that Artificial Neural Networks have the ability to predict the soil classification and soil parameters in the Blue Nile Area of Khartoum with an acceptable degree of accuracy.
Description: Prediction Of Blue Nile Profile Using Artificial Intelligence Technique
URI: http://hdl.handle.net/123456789/5065
Date: 2014-11-11


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