舆情扩散环境下的应急资源需求预测研究

摘要随着全球社会经济的高速发展，人口、环境、资源以及公共卫生等方面的问题日益严重，各种突发性疫情事件对社会的危害形势也日趋严峻。应对突发性疫情事件是一项复杂的系统工程，其中在疫情发生后对疫情扩散规律的研究和应急资源的需求预测更是关乎控制成效，保障人民生命安全和维持社会安定的重要方面。因此，如何科学地研究对疫情扩散规律，合理有效的应急资源的需求的预测，是提高突发公共卫生事件预警防御系统稳定性、可靠性和时效性的关键问题。65175

本文在国内外研究现状分析的基础上，以SARS的传染病流行所引发的疫情扩散环境下的应急资源需求预测为研究对象，进行了以下几方面的研究。首先，在SARS传染病扩散环境下用Logistic 回归模型进行扩散规律研究，通过建立Logistic回归模型对所收集的数据进行Matlab编程拟合，在此基础上，建立应急物资需求与患者人数的函数关系。其次，建立了集成ARIMA和NN的传染病疫情扩散预测模型，对北京地区SARS患者治愈人数时间序列实际数据进行验证，同时建立应急物资需求与累积治愈人数的函数关系，最终实现了对疫情扩散环境下的应急资源需求预测研究。

关键词：疫情扩散规律应急资源需求预测 Logistic回归 ARIMA模型 ARIMA-NN模型

毕业论文外文摘要

Title A study of demand forecast of emergency resources in the epidemic diffusion environment

Abstract

With the rapid economic development of the global community，the problem，including population，environment，resources and public health and something like these，are growing increasingly severe。 The harm which all kinds of unexpected events of the epidemic situation bring to society also are becoming increasingly severe。The solve of emergent outbreak event is a complex system engineering。The research of epidemic diffusion and the demand forecast of emergency resource are significant to control the effectiveness，protect people's lives and maintain social stability after the outbreak。Therefore，the scientific study of the law of epidemic spread and the reasonable forecasts of the demand of the emergency resource are the key issues to improve the stability，reliability and timeliness of the system of public health emergency warning。

Based on the Chinese research and the foreign study ，this paper regards the demand forecast of the emergency resources which the SARS caused in the environment of the spread of the epidemic as the object，carried out the following studies。First，we research the diffusion law through the Logistic regression model in the SARS epidemic environment，and make the Matlab programming fit with the data that the Logistic regression model collects。Finally，we establish the appropriate function of the patient and the resource demand。By ARIMA-NN prediction model for SARS patients in Beijing cure actual number of time-series data of the proposed integrated model was validated， and finally establish the appropriate function of the resource demand and the number ,and ultimately the spread of the epidemic environment for emergency resource demand prediction。

Keywords Logistic Regression ARIMA Mode ARIMA-NN ModeSpread of the Epidemic Regularity Demand Forecast of Emergency Resource

目录 1

第一章绪论 1

1.1 研究背景和意义 1

1.1.1 研究背景 1

1.1.2 意义舆情扩散环境下的应急资源需求预测研究:http://www.youerw.com/guanli/lunwen_72671.html