模糊神经网络用于SARS疾病疫情非线性系统的辨识和预报

论文提出了模糊神经网络用于SARS疾病疫情非线性系统建模和预报的思想,同时该方法可以推广到各种流行性疾病的预防和控制中。模糊神经网络是近年来发展起来的新兴学科,它主要应用于非线性系统的建模、预报和控制,特别适合于不同输入类型的模型系统。而流行性疾病的传播规律较好地与模糊神经网络模型特点相符合,所以在这里提出用模糊神经网络用于SARS疾病疫情非线性系统的辩识和预报的观点,相应的也可推演到其它流行性疾病传播规律中。

Fuzzy Neural Networks Using to Distinguish and Forecast Non-linearity Systems of SARS Epidemic Situation

This thesis puts fo rw ard one idea of fuzzy neural networks using to distinguish and forecast non-lin earity Systems of SARS epidemic situation,at the same time ,the method can g eneralize to defend and control on apiece epi-demic.Fuzzy neural networks is a new subject in close years,it mostly applies to modeling,forecasting and cont rolling non-linearity systems ,especially is propitious to model-system of va ry inputting style.The spread rule of epidemic ac-cord with the characteristic of fuzzy neural networks model,so this thesis puts forward the viewpoint of f uzzy neural networks using to distinguish and forecast non-linearity systems o f SARS epidemic situation,it also can deduce to spread rule of other epidemic.