Artificial Neural Networks Approach for Electrochemical Resistivity of Highly Organic Soil

摘要

The resistivity of highly organic soils was measured using electrochemical resistivity reactor. Artificialneural networks (ANNs) were developed for the prediction of the resistivity at the different organiccontent, porosity, water content, and temperature. The results of study revealed that the resistivity ofthe highly organic soil decreased as the water content or temperature increased. The study showed thatthe resistivity of highly organic soil was also affected by degree of humification. As the degree of peathumification increased, the resistivity decreased. It was also concluded that the constructed ANNsmodels exhibited high performance for predicting of the resistivity of the highly organic soils.