A Time-Varying Data Classification Approach Based on ANN with Slide-Window
Ai Ping Chai · Applied Mechanics and Materials · 2013
Time-varying data widely exists anywhere in the objective world, and whose diverse distribution as time is a hybrid stochastic process. Whereas, determining how to achieve knowledge from time-varying database is still an important content of data-mining. In fact, existing techniques of data-mining are difficult to deal with this problem. The paper deeply studies and analyses finite dimension distribution function families of stochastic process and gives out existent theorem of time-varying data classification, proposes a new more effective technique called time-varying datasets classification approach based on slide-window neural networks, and gives out smoothing algorithm and convergent condition with solving this problem as well as simulation examples. The result shows the proposed method is a very effective time-varying data classification method.