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KDD
2009
ACM
364views Data Mining» more  KDD 2009»
14 years 8 months ago
Causality quantification and its applications: structuring and modeling of multivariate time series
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Takashi Shibuya, Tatsuya Harada, Yasuo Kuniyoshi
KES
2010
Springer
13 years 5 months ago
Evolving takagi sugeno modelling with memory for slow processes
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with lo...
Simon McDonald, Plamen P. Angelov
IDEAL
2004
Springer
14 years 24 days ago
Combining Local and Global Models to Capture Fast and Slow Dynamics in Time Series Data
Many time series exhibit dynamics over vastly different time scales. The standard way to capture this behavior is to assume that the slow dynamics are a “trend”, to de-trend t...
Michael Small
IDA
2009
Springer
14 years 2 months ago
Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences
Abstract. This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes techniques as a complementary step to the model....
Francisco Martínez-Álvarez, Alicia T...
ICDE
2003
IEEE
211views Database» more  ICDE 2003»
14 years 8 months ago
Capturing Sensor-Generated Time Series with Quality Guarantees
We are interested in capturing time series generated by small wireless electronic sensors. Battery-operated sensors must avoid heavy use of their wireless radio which is a key cau...
Iosif Lazaridis, Sharad Mehrotra