We are developing several data mining techniques for (i) autonomous detection of boundaries and (ii) to derive nonlinear analytical models from timeseries data.  In the latter case, we are finding more accurate results than other techniques such as artificial neural net and genetic programming at significantly lower computational cost.

Reverse Engineering of Time Series Data

Example of Application to Modeling of Magnetopause

Pattern Recognition

Example of Application to Detection of Magnetopause Crossings