Artificial Intelligence-Based Algorithm for Energy Exposure Analysis in Composite Material

For massive dosimetry analysis of finite composite materials (CMs), an effective approach is proposed based on the artificial intelligence (AI) computational algorithm. Machine learning (ML) method is used to analyze systematic energy characteristics of finite CM for dosimetry exposure. To prove the validity of our algorithm, we analyzed a finite CM in a specific scenario and calculated its exposure dosimetry. The dataset for algorithm training is obtained through numerical analysis. In order to verify the efficiency of the proposed method, the accuracy of this algorithm and its time consumption are calculated. Five ML methods are subsequently used to compare the average absorption of the energy resonance exposure in the finite CM. The time consumption and error distribution in test sets prove the high efficiency of AI computational algorithm to analyze the energy exposure of finite CM. The proposed AI algorithm is useful for the massive numerical analysis in the research of electromagnetic (EM) exposure.