Uncertainty Forecasting in Engineering

Description

This book provides an introduction to uncertainty forecasting based on fuzzy time series. Observations of uncertainty in measured data with time improves forecasting capability in a wide range of fields such as civil engineering and environmental science. Uncertain data are described by means of a completely new incremental fuzzy representation that allows the complete and accurate estimation of uncertainty by combining description, modeling, and forecasting of fuzzy time series for the first time.

Descriptive, modeling, and forecasting methods for fuzzy time series are introduced and explained in detail. Emphasis is placed on forecasting based on fuzzy random processes such as fuzzy ARMA processes and fuzzy white-noise processes as well as forecasting involving fuzzy neuronal networks.

The fact that all numerical algorithms are clearly described and demonstrated by way of examples means that they may be directly implemented for practical applications. This is shown by means of practical examples.
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