ES-BP联合模型预测中国大陆1982-2020年梅毒发病率的研究。

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Daren Zhao
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引用次数: 0

摘要

背景:在中国,梅毒仍是一个主要的公共卫生问题。我们旨在构建一个预测梅毒流行趋势的最佳模型,并为预防和控制提供有效的预防措施。方法:从《中国卫生统计年鉴》中获得1982-2020年梅毒发病率数据。建立了指数平滑模型(ES模型)和BP神经网络模型,并在此基础上建立了ES-BP组合模型。通过比较平均绝对误差(MAE)、均方误差(MSE)、平均绝对百分比误差(MAPE)和均方根误差(RMSE)来评估预测性能,其残差为白噪声序列(P=0.359)。最优BP神经网络模型有三层,输入层、隐藏层和输出层的节点数分别为5、11和1,五次交叉验证的MAE、MSE和RMSE的平均值分别为1.519、6.894和1.969。ES-BP组合模型有三层,分别为模型节点1、4和1。通过五次交叉验证获得的MAE、MSE和RMSE的最低平均值分别为1.265、5.739和2.105。结论:ES、BP神经网络和ES-BP组合模型可用于预测梅毒发病率,但ES-BP联合模型的预测性能优于基本ES模型和基本BP神经网络模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Research of Combined ES-BP Model in Predicting Syphilis Incidence 1982-2020 in Mainland China.

Research of Combined ES-BP Model in Predicting Syphilis Incidence 1982-2020 in Mainland China.

Research of Combined ES-BP Model in Predicting Syphilis Incidence 1982-2020 in Mainland China.

Research of Combined ES-BP Model in Predicting Syphilis Incidence 1982-2020 in Mainland China.

Background: Syphilis remains a major public health concern in China. We aimed to construct an optimum model to forecast syphilis epidemic trends and provide effective precautionary measures for prevention and control.

Methods: Data on the incidence of syphilis between 1982 and 2020 were obtained from the China Health Statistics Yearbook. An exponential smoothing model (ES model) and a BP neural network model were constructed, and on this basis, the ES-BP combination model was created. The prediction performance was assessed to compare the MAE (Mean Absolute Error), MSE (Mean Squared Error), MAPE (Mean Absolute Percentage Error), and RMSE (Root Mean Square Error).

Results: The optimum ES model was Brown's linear trend model, which had the lowest MAE and MAPE values, and its residual was a white noise sequence (P=0.359). The optimum BP neural network model had three layers with the number of nodes in the input, hidden, and output layers set to 5, 11, and 1, and the mean values of MAE, MSE, and RMSE by five-fold cross-validation were 1.519, 6.894, and 1.969, respectively. The ES-BP combination model had three layers, with model nodes 1, 4, and 1. The lowest mean values of MAE, MSE, and RMSE obtained by five-fold cross-validation were 1.265, 5.739, and 2.105, respectively.

Conclusion: The ES, BP neural network, and ES-BP combination models can be used to predict syphilis incidence, but the prediction performance of the ES-BP combination model is better than that of a basic ES model and a basic BP neural network model.

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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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