The preventive cultural relics protection is one of the most concerned contents in archaeology, which includes environmental monitoring and accurate prediction of cultural relics diseases. In view of the deficiency of the analysis of cultural relics data and the prediction of cultural relics diseases, a prediction model of immovable cultural relics diseases based on relevance vector machine (RVM) is proposed. The key factors affecting the disease of immovable cultural relics are found out by the principal component analysis method, and the dimension reduction of data is realized; then, the RVM model under the framework of Bayesian theory is constructed, and the super parameters are estimated by the maximum edge likelihood method; finally, the prediction accuracy of the model is compared with the traditional diseases prediction methods. The experiment results demonstrate that the proposed RVM-based immovable cultural relics disease prediction approach not only has the advantages of more sparse model but also has better prediction accuracy than the traditional radial basis function neural network-based and support vector machine-based methods.

中文翻译：

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基于关联向量机的固定文物疾病预测

预防性文物保护是考古学最关注的内容之一，包括环境监测和对文物疾病的准确预测。针对文物数据分析和文物疾病预测的不足，提出了一种基于相关向量机（RVM）的不动产文物疾病预测模型。用主成分分析法找出影响固定文化遗产病害的关键因素，实现数据降维；然后，在贝叶斯理论框架下构建RVM模型，并通过最大边缘似然法估计超参数。最后，将该模型的预测精度与传统疾病的预测方法进行了比较。