Expert system for the characterization of laboratory sample input signals: AUTOCORR
Paul J.H.C. Mijland, Jo Klaessens, Bernard G. M. Vandeginste, Gerrit Kateman · Journal of Chemometrics · 1989
Abstract An expert system is presented for automated time series analysis of laboratory sample input signals. The system, AUTOCORR, builds a model of the time series by identifying the processes that are present. These are an uncorrelated random process and, underlying this, possibly one or more of the following: a first‐order autoregressive process, a trend and a periodic process. AUTOCORR has a knowledge base of 44 rules and 41 facts for this purpose. The employed shell, INFER, allows the use of algorithmic procedures. Elaborate tests with simulated signals show that AUTOCORR has a very low false positive score and is successful in describing time series for laboratory simulation models.