提出了一种防御SARS这样的突发疾病的智能决策支持系统。通过运用新的数据分析和决策支持理论，建立智能的决策支持系统，对现有的疫情进行数据噪声分析、灾变趋势预测以及提出科学决策。系统主要分噪声子系统、预测和模拟子系统、诊断子系统以及二次防御子系统4部分。其中预测子系统以FGR系统为原型，综合了传统微分方程的预测方法，以及基于数据的包括神经网络、支持向量机的方法和模糊推理方法的综合信息处理系统，经过该系统的预测分析和模拟可以对可变的突发疫情进行更科学的决策。

This paper presents an intelligence decision supporting system to prevent and control such disease like SARS. Using some new decision supporting theories, an intelligent decision supporting system can be created to conduct the noise analysis of SARS epidemic situation, forecast the evolution direction of the epidemic, and give proper solution. The system is divided into four parts： noise analysis subsystem, forecast and simulate subsystem, treatment and control subsystem and second recovery subsystem. The forecast subsystem is based on FGR system, which combines forecast methods of traditional differential equations with data analysis.