## Abstract We consider the problem of forecasting a stationary time series when there is an unknown mean break close to the forecast origin. Based on the intercept‐correction methods suggested by Clements and Hendry (1998) and Bewley (2003), a hybrid approach is introduced, where the break and bre
A hybrid fuzzy-fractal approach for time series analysis and plant monitoring
✍ Scribed by Oscar Castillo; Patricia Melin
- Publisher
- John Wiley and Sons
- Year
- 2002
- Tongue
- English
- Weight
- 312 KB
- Volume
- 17
- Category
- Article
- ISSN
- 0884-8173
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✦ Synopsis
We describe in this article a new hybrid fuzzy-fractal approach for plant monitoring. We use the concept of the fractal dimension to measure the complexity of a time series of observed data from the plant. We also use fuzzy logic to represent expert knowledge on monitoring the process in the plant. In the hybrid fuzzy-fractal approach, a set of fuzzy if-then rules are used to classify different conditions of the plant. The fractal dimension is used as an input linguistic variable in the fuzzy system to improve the accuracy in the classification. An implementation of the proposed approach is shown to describe in more detail the method.
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