通过使用机器学习分析,识别北卡罗来纳州住宅度空间时间变化的预测因素
Zhenchun Yang1, Lauren Prox2, Clare Meernik3
1Duke Global Health Institute, Durham, NC, 27708, United States.
造成肺癌风险的气受到海拔高度,土壤水分和地质断层的接近程度的影响. 这项研究使用了广泛的数据和机器学习来识别室内水平的关键环境预测因素.
科学领域:
- 环境科学 环境科学
- 地质地质地质地质地质地
- 公共卫生 公共卫生
背景情况:
- 是一种天然存在的放射性气体,与肺癌有关.
- 住宅中的暴露是严重的公共卫生问题.
- 了解的环境预测因素对于暴露评估至关重要.
研究的目的:
- 推进评估住宅暴露的方法.
- 为了确定室内度的关键环境预测因素.
- 提高水平预测的准确性和可靠性.
主要方法:
- 利用了来自北卡罗来纳州 (2010-2020) 的126,382个短期子测试结果的大数据集.
- 采用线性回归,线性混合效应模型 (LME) 和通用添加模型 (GAM).
- 应用随机森林模型来识别有影响力的环境预测因素.
主要成果:
- 在所有统计模型中,海拔显示与水平有着一致的正相关性.
- 接近地质断层与度负相关.
- 随机森林分析确定了海拔,表面压力和土壤水分作为最有影响力的预测因素.
结论:
- 高度,地质接近和土壤水分是决定度的关键因素.
- 气候和土壤/植被动态也显著影响变异性.
- 综合建模方法提高了对住宅水平的理解和预测.
更多相关视频
14:27Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
相关概念视频
Steps in Outbreak Investigation
Residuals and Least-Squares Property
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Mechanistic Models: Compartment Models in Individual and Population Analysis
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Regression Analysis
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
