A New Insight Into Prediction Modeling Systems

Authors:
Sang C. Suh;Sam I. Saffer;Dan Li;Jingmiao Gao
Affiliations:
Department of Computer Science, Texas A&M University-Commerce, Commerce, TX 75428, USA;Department of Computer Science, Texas A&M University-Commerce, Commerce, TX 75428, USA;Department of Computer Science, Texas A&M University-Commerce, Commerce, TX 75428, USA;Department of Computer Science, Texas A&M University-Commerce, Commerce, TX 75428, USA
Venue:
Journal of Integrated Design & Process Science
Year:
2004

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Abstract

Data mining and forecasting has attracted a lot of research interest in time series data sequence. The paper brings a new insight in how to select different time series forecasting models to make prediction according to different situations and data patterns. The contribution of this research is to facilitate prediction modelling system design for extensive forecasting purpose.