Among multiple seismic attributes,the in-stantaneous amplitude,instantaneous frequency ,in-stantaneous phase and coherent data volume as well as waveform clustering can be basically de-fined as basi.

To overcome volatility clustering problems,an adaptive neuro-fuzzy inference system(ANFIS) is combined with a nonlinear generalized autoregressive conditional heteroscedasticity(NGARCH) model that is tuned by adaptive support vector regression(ASVR) so as to tackle the problem of time-varying conditional variance in residual errors.

On the basis of characteristic of price behavior in stock market,that is,three typical characteristics of the financial time series(fat tails,excess kurtosis,volatility clustering),intertemporal dependence models widely used internationally were verified,i.

Implementation of MPI-based parallel wavecluster algorithm on Shuguang TC1700;

Mining Temporal Patterns of Stock Yield Sequences Based on Wave Cluster Method;

To achieve a graph abstraction,a hierarchical clustered graph is extracted from a general large graph based on the community structures discovered in the graph.