Prediction of swelling pressure of soil using artificial intelligence techniques
 Sarat Kumar Das,
 Pijush Samui,
 Akshaya Kumar Sabat,
 T. G. Sitharam
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The swelling pressure of soil depends upon various soil parameters such as mineralogy, clay content, Atterberg’s limits, dry density, moisture content, initial degree of saturation, etc. along with structural and environmental factors. It is very difficult to model and analyze swelling pressure effectively taking all the above aspects into consideration. Various statistical/empirical methods have been attempted to predict the swelling pressure based on index properties of soil. In this paper, the computational intelligence techniques artificial neural network and support vector machine have been used to develop models based on the set of available experimental results to predict swelling pressure from the inputs; natural moisture content, dry density, liquid limit, plasticity index, and clay fraction. The generalization of the model to new set of data other than the training set of data is discussed which is required for successful application of a model. A detailed study of the relative performance of the computational intelligence techniques has been carried out based on different statistical performance criteria.
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 Title
 Prediction of swelling pressure of soil using artificial intelligence techniques
 Journal

Environmental Earth Sciences
Volume 61, Issue 2 , pp 393403
 Cover Date
 20100701
 DOI
 10.1007/s1266500903526
 Print ISSN
 18666280
 Online ISSN
 18666299
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 Expansive soil
 Swelling pressure
 Artificial neural network
 Support vector machine
 Industry Sectors
 Authors

 Sarat Kumar Das ^{(1)}
 Pijush Samui ^{(2)}
 Akshaya Kumar Sabat ^{(3)}
 T. G. Sitharam ^{(4)}
 Author Affiliations

 1. Department of Civil Engineering, National Institute of Technology, Rourkela, 769008, India
 2. Department of Civil Engineering, Tampere University of Technology, Tampere, Finland
 3. Department of Civil Engineering, KIIT University, Bhubaneswar, 751024, India
 4. Indian Institute of Science, Banglore, 560012, India