Construction of Digital Models for Predicting the Specific Electrical Resistivity of a Polymer Composite Using Contemporary Intelligent Data Analysis
摘要
Digital models of a polypropylene−technical-carbon (PP−TC) polymer composite material (CM) were constructed. The input parameters and output parameter, i.e., specific bulk electrical resistance, were established based on the physical properties of the matrix and filler. A neural network model was constructed to predict the CM conductivity. Scattering diagrams showed that the trained neural network gave highly accurate predictions. The most significant structural characteristics for CM conductivity were identified.