Predictive System for Multivariate Time Series
نویسندگان
چکیده
The paper is focused on the analysis and design of multivariate time series prediction systems. It addresses mainly practical issues, the main contribution is the developed and implemented conceptual predictive methodology. It is based on designed data management structures that define basic data flow. Despite the fact that the methodology is inspired by problems common for utility companies that distribute and control the transport of their applicable commodity, it may be considered as a general methodology. Currently, the predictive methodology combines several prediction techniques, such as regression by means of singular value decomposition, support vector machines and neural networks. Data management structures are open to other predictive algorithms as well. The methodology is implemented in the form of a software tool. It is verified on a real-life prediction task— prediction of the daily gas consumption of regional gas utility companies.
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