Implementation of an Artificial Neuro-Electronic System for Moisture Content Determination of Subbase Soil

Abstract

In this paper, a new approach will be proposed to determine the moisture content of subbase soil in a view to suppress the limitations of existing methods while maintaining the better accuracy. This innovation embeds an automatic electronic control as well as an artificial neural network (ANN) in the framework for time optimization. Artificial neural network and automatic electronic control both together can be termed as artificial neuro-electronic control. The artificial neural network has been trained by mapping the weights of soil samples at specific time steps to the respective final moisture contents. As a result, the system can be able to predict the final moisture content by analysing fewer data samples in the very be- ginning of moisture content determination tests. Validation of the predictive results has also been conducted in real time for soil samples suitable for subbase layer of a pavement to ensure the system feasibility for laboratory and field uses. Experiments show that this fully automatic system can exhibit a significant accuracy and precision for the evaluation of moisture content in about 50% reduced time compared to the standard microwave based method.