CAJ | 학술논문

针对古陶瓷断源断代的研究目的，以景德镇仿龙泉青瓷与龙泉青瓷胎的化学组成为研究对象，选择了多元统计判别分析方法、人工神经网络算法对其进行数据处理分析和产地判别研究，并将多元统计判别分析和人工神经网络进行对比分析，探讨了不同方法之间的差异性及适用性。结果表明，由于古陶瓷元素组成数据难以完全满足多元统计判别分析对于数据变量的要求，因而多元统计判别分析相对于人工神经网络的判别正确率较低，人工神经网络更适合用于古陶瓷断源断代研究。
침대고도자단원단대적연구목적，이경덕진방룡천청자여룡천청자태적화학조성위연구대상，선택료다원통계판별분석방법、인공신경망락산법대기진행수거처리분석화산지판별연구，병장다원통계판별분석화인공신경망락진행대비분석，탐토료불동방법지간적차이성급괄용성。결과표명，유우고도자원소조성수거난이완전만족다원통계판별분석대우수거변량적요구，인이다원통계판별분석상대우인공신경망락적판별정학솔교저，인공신경망락경괄합용우고도자단원단대연구。
The chemical composition test results of the body of Jingdezhen imitated Longquan and Longquan celadon were studied by multivariate statistical discriminant analysis and artiifcial neural networks for their respective provenance and chronology. The differences and applicability of the two methods were discussed. Results show that as the data of ancient ceramic element composition couldn’t fully meet its requirements, the accuracy of the multivariate statistical discriminant analysis is lower than that of the artiifcial neural networks, which means the artiifcial neural networks is more suitable for ancient ceramic provenance and chronology determination.