Artificial neural network models for predicting electrical resistivity of soils from their thermal resistivity

摘要: The knowledge of soil electrical and thermal resistivities is essential for several engineering projects such as laying high voltage buried power cables, nuclear waste disposal, design fluidized beds, ground modification techniques etc. This necessitates precise determination these resistivities, relationship between them, which mainly depend on the type, its origin, compaction density saturation. Such a would also be helpful determining one if other known. With this in view, efforts were made to develop artificial neural network (ANN) models that can employed estimating resistivity based degree To achieve this, measurements carried out different types soils compacted at densities moisture contents. These validated by comparing predicted results vis-a-vis those obtained from experiments. efficiency ANN predicting has been demonstrated, are found yield better compared generalized relationships proposed earlier researchers.