Predicting CBR Value from Index Properties of Soils using Expert System

Ahmad Taha Abdulsadda

Predicting CBR Value from Index Properties of Soils using Expert System

Ahmad Taha Abdulsadda * §

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§ Al Najaf technical Institute

Predicting CBR Value from Index Properties of Soils using Expert System

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Abstract

The sub grade gives an establishment to supporting the asphalt structure. The sub review regardless of whether in cut or fill ought to be all around compacted to use its full quality and to conserve consequently on the general thickness of asphalt required. For plan, the sub review quality is evaluated regarding the CBR of the sub review soil in both fill and cut areas. For deciding the CBR esteem, the static entrance test method ought to be entirely clung to. The test should dependably be performed on formed specimens of soils in the research center. CBR test is difficult and tedious; yet once in a while the outcomes are not precise due to the poor laboratory conditions. Advance if the accessible soil is of low quality, appropriate added substances are blended with soil and the subsequent quality of the dirt will be evaluated by CBR esteem, which is unwieldy. In this paper we proposed a new expert system (Multi Layer Perceptron (MLP) neural network) to be working as computer decision maker and predicate the precise CBR value based upon the data.

References

13 Cites in Article

Reference Format

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Ahmad Taha Abdulsadda. 2017. "Predicting CBR Value from Index Properties of Soils using Expert System". Global Journal of Research in Engineering - E: Civil & Structural GJRE-E Volume 17 (GJRE Volume 17 Issue E1).

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GJRE Volume 17 Issue E1

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

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Classification

GJRE-E Classification FOR Code: 290899

Submission ReceivedDecember 6, 2016
Peer Review Double Blind
Handling Editor
Accepted December 31, 2016
Published January 15, 2017

Version of record

v1.2

Issue date

August 11, 2017

Language

English

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Article Matrices

Total Score: 102

Country: Iraq

Subject: Global Journal of Research in Engineering

Authors: Ahmad Taha Abdulsadda, Dhurgham Abdul Jaleel (PhD/Dr. count: 0)

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Publish Date: 2017 01, Sun

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