Exponential prediction models based on sequence operators
| Autor: | Sifeng Liu, Achim Sydow, William Mennell, Roman DeNu, Yi Lin |
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| Přispěvatelé: | Publica |
| Předmět: |
Sequence
Series (mathematics) business.industry Regression analysis Classification of discontinuities Machine learning computer.software_genre Theoretical Computer Science Order of integration Exponential function Control and Systems Engineering Outlier Computer Science (miscellaneous) Artificial intelligence Time series business Engineering (miscellaneous) Algorithm computer Social Sciences (miscellaneous) Mathematics |
| Zdroj: | Scopus-Elsevier |
| Popis: | One of the difficulties experienced in applications of exponential prediction models of time series is resolved by introducing sequence operators. This approach is different from all known modelings of time series and regression analysis. Also, discontinuities (or outliers), appearing in a given time series, can be naturally absorbed by applying sequence operators. This end is important since, in terms of predictions, outliers or discontinuities in the data might signal major changes in the pattern of the time series data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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