On the identification of compaction characteristics by neuronets

Abstract Compaction of soils is aimed at modifying their engineering properties to fulfil the needs of earthwork projects. The two characteristic compaction parameters, namely the optimum moisture content and the maximum dry density, can only be determined experimentally. In this paper, neuronets have been developed and used to determine these two parameters from variables pertinent to geotechnical engineering soil properties and indices. The predictions of the various developed neuronets are compared with corresponding actual values and values obtained via statistical correlation models. Moreover, the advantages of neuronets as prediction techniques over the conventional regression methods are addressed.

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