A Visualization Model for Time Series Analysis of Data
Sunil Bhaskarana · 2011
Time series data mining can be treated as an sub set of data mining and it is important in the fields of economics, medical science, manufacturing segments, space technology etc. In this paper we propose a new method for the pattern visualization. The multiple time-series problem of modeling and predicting simultaneous movements of a collection of time-sensitive variables that are related to each other has received much less attention. The visualization technique we proposed is basically converts a physical action to a set of time variable sequential data. The key challenge is how to capture the multiple time series data simultaneously. Study revealed that the global and local models specially developed for multiple time-series prediction outperformed methods such as multiple linear regression and the multilayer perception that were developed for predicting single time series.