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统计学预测模型列线图在眼科的应用 被引量:4
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作者 惠延年 《国际眼科杂志》 CAS 北大核心 2023年第7期1061-1063,共3页
列线图又称诺莫图,是通过多因素回归分析得出各相关因素对结局变量的影响力,构建并用于预测事件风险(如诊断或预测疾病发展与后果等)的统计学预测模型。列线图将复杂的回归方程转变为直观、容易理解的可视化图形,便于评估患者病情与医... 列线图又称诺莫图,是通过多因素回归分析得出各相关因素对结局变量的影响力,构建并用于预测事件风险(如诊断或预测疾病发展与后果等)的统计学预测模型。列线图将复杂的回归方程转变为直观、容易理解的可视化图形,便于评估患者病情与医患沟通。随着医学科技的飞速发展和个性化医疗需求增加,其在临床医学已得到越来越多的关注和广泛应用。本篇短文介绍列线图的基本概念以及在眼科应用的例子。 展开更多
关键词 列线图 统计学预测模型 眼科学
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Mine water discharge prediction based on least squares support vector machines 被引量:1
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作者 GUO Xlaohui MA Xiaoping 《Mining Science and Technology》 EI CAS 2010年第5期738-742,共5页
In order to realize the prediction of a chaotic time series of mine water discharge,an approach incorporating phase space reconstruction theory and statistical learning theory was studied.A differential entropy ratio ... In order to realize the prediction of a chaotic time series of mine water discharge,an approach incorporating phase space reconstruction theory and statistical learning theory was studied.A differential entropy ratio method was used to determine embedding parameters to reconstruct the phase space.We used a multi-layer adaptive best-fitting parameter search algorithm to estimate the LS-SVM optimal parameters which were adopted to construct a LS-SVM prediction model for the mine water chaotic time series.The results show that the simulation performance of a single-step prediction based on this LS-SVM model is markedly superior to that based on a RBF model.The multi-step prediction results based on LS-SVM model can reflect the development of mine water discharge and can be used for short-term forecasting of mine water discharge. 展开更多
关键词 mine water discharge LS-SVM chaotic time series phase space reconstruction PREDICTION
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