Description

ABSTRACT

•      Since in ancient time the sequential and time series remains an important problem

•      Despite progress in other related fields how efficiently cluster classify and predict the trends of these data is still an open problem

•      And particularly the major problem is the noise in the time series data

•      Many time series used for predictions are contaminated by noise making it difficult to do accurate short term and long term predictions

•      Although signal processing techniques such as wavelet analysis and filtering can be applied to remove the noise they often introduce lags in the filtered data