模糊模式识别在房地产预警信息系统中的应用

本文利用模糊模式识别和主成分分析等方法，进行房地产预警实证分析。以南京房地产市场为例说明。在面对若干繁冗驳杂的一系列指标时，如何进行指标归类，建立一套指标体系，以及如何分析这些指标反映的房地产市场所处的警情的层面。从而适时的得出一些分析结果，以供管理者做出及时的政策调整，避免房地产业危机的产生。     

Transport mechanism of reverse surface leakage current in AlGaN/GaN high-electron mobility transistor with SiN passivation

The transport mechanism of reverse surface leakage current in the AlGaN/GaN high-electron mobility transistor(HEMT) becomes one of the most important reliability issues with the downscaling of feature size.In this paper,the research results show that the reverse surface leakage current in AlGaN/GaN HEMT with SiN passivation increases with the enhancement of temperature in the range from 298 K to 423 K.Three possible transport mechanisms are proposed and examined to explain the generation of reverse surface leakage current.By comparing the experimental data with the numerical transport models,it is found that neither Fowler-Nordheim tunneling nor Frenkel-Poole emission can describe the transport of reverse surface leakage current.However,good agreement is found between the experimental data and the two-dimensional variable range hopping(2D-VRH) model.Therefore,it is concluded that the reverse surface leakage current is dominated by the electron hopping through the surface states at the barrier layer.Moreover,the activation energy of surface leakage current is extracted,which is around 0.083 eV.Finally,the SiN passivated HEMT with a high Al composition and a thin AlGaN barrier layer is also studied.It is observed that 2D-VRH still dominates the reverse surface leakage current and the activation energy is around 0.10 eV,which demonstrates that the alteration of the AlGaN barrier layer does not affect the transport mechanism of reverse surface leakage current in this paper.