泗水市肺结核病例通报率预测的模糊线性回归

S. Halim, R. Intan, L. P. Dewi
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引用次数: 1

摘要

本文讨论了用模糊线性回归预测泗水市结核病病例通报率的方法。这种疾病的预测是非常重要的,因为结核病是一种带有污名的疾病,因为它具有潜在的高度传染性。在本研究中,我们首先描述了病例通报率(CNR)的统计数据,特别是2017年的统计数据。我们根据每个地区的贫困百分比对男性、女性和总数的农村人口比例进行了分类。基于这种聚类,我们可以绘制出结核病发病率和贫困率高、中、低的地区。利用Moran I的统计数据,对区域间的空间依赖性进行了检验。因此,在试验结果的基础上,本研究还考虑了一个地区对其他地区传播疾病的空间效应,并采用模糊线性回归模型进行预测。该模型具有较好的预测效果,模型的均方误差为835.87,平均绝对偏差为22.46
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy linear regression for tuberculosis case notification rate prediction in Surabaya
In this paper we discuss the fuzzy linear regression for predicting the Tuberculosis (TB) case notification rate prediction in Surabaya. The prediction of this disease is very important since TB is among the diseases that carries stigma because it is potentially highly contagious. In this research, we first describe the statistics for the case notification rate (CNR), particularly for the year 2017. We cluster the CNR for man, woman and total with respect to the poverty percentage in each district. Based on this clustering we can map in which district the Tuberculosis CNR and the poverty percentage is high, medium and low. Using the Moran I' statistics, we then tested the spatially dependency among the district. Based on the test result therefore, in this research we also regard the spatial effect of a district to the others in spreading the disease, and model the prediction using fuzzy linear regression. The model can predict good, the mean square error of the model is 835.87 and the mean absolute deviation is 22.46
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