Prediction of Optimum Moistiure Cntent using Genetic Algorithm

Fasna M B, Fathima Zuhara T. N., Sowmya V. Krishnankutty

Abstract


A genetic model for the prediction of compaction parameter ‘Optimum moisture content’ is developed in this project. It is difficult to obtain OMC directly from the field, because it needs lot of effort and time by using laboratory method. The development of OMC from index properties of soils helps to reduce this effort. The considered index properties in this project are liquid limit, plastic limit, percentage fines, percentage sands, percentage gravels and specific gravity. The development and verification of the genetic model was done using a large database with 200 case histories from various sources and Geo Technical Engineering Laboratories from Ernakulum district, Kerala. The dataset mainly is of c-Փ soils. The correlation of predicted data with actual measurements was found out and got to know that the genetic algorithm method have good degree of accuracy.

                          


Keywords


Optimum Moisture Content; Genetic Model; c-Փ soil; index properties

Full Text:

PDF

References


C M Chan, L M Zhang, and Jenny T Ng, “Optimization of Pile Groups Using Hybrid Genetic Algorithms.” Journal of Geotechnical and Geoenvironmental Engineering., vol. 135, no. 4, pp. 497–505, 2009.

Al-Khafaji A.N, “Estimation of soil compaction Parameters by means of atterberg limit” Q. J. Eng. Geol. Hydrogeol., vol.26, no.4, pp. 359-368, 1993.

Culshaw, M. G, "The provision of digital spatial data for engineering geologists", Bull Eng Geol Env, pp: 185–194, 2006.

Blotz L, Bension, C. and Boutwell, G., “Estimating optimum water content and max.dry unit weight for compacted soils” J. Geotech Geoenvir Engg., vol.124, no. 9, pp. 907-912, 1998.

Maziar Pasdarpour a, Mahmoud Ghazavi., “Optimal design of soil dynamic compaction using genetic algorithm and fuzzy system”, journal of Soil Dynamics and Earthquake Engineering., vol. 29, pp. 1103-1112, 2009.

A. Johari , A.A. Javadi , G. Habibagahi., “Modelling the mechanical behaviour of unsaturated soils using a genetic

algorithm-based neural network”, journal of Computers and Geotechnics., vol. 38, pp. 2-13, 2011.




DOI: https://doi.org/10.24203/ajet.v5i3.4746

Refbacks

  • There are currently no refbacks.


Copyright (c) 2017 Asian Journal of Engineering and Technology

Creative Commons License
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.