An up-to-date introduction to possibility theory. An integrated view on uncertainty techniques based on multi-valued mappings, fuzzy relations and random sets. Adoption of concepts into a temporal environment characterised by signal or data processing. Illustration of the application of possibility theory to data analysis in process and supervisory control systems with examples taken from the area of condition monitoring. Set theory and logic are the basic theoretical tools for modelling and reasoning. Their application to real-world problems induces various types of uncertainty Related to the observation of processes, the measurement of signals and the mismatch between mathematical models and the real world in general. Possibility theory provides a framework in which all forms of uncertainty can be represented. This book reviews, extends and applies possibility theory in an integrated approach that combines probability theory, statistical analysis and fuzzy mathematics.
Set theory and logic are the basic theoretical tools for modelling and reasoning. Their application to real-world problems induces various types of uncertainty related to the observation of processes, the measurement of signals and the mismatch between mathematical models and reality in general.
Various distinct forms of uncertainty such as randomness, vagueness, fuzziness, ambiguity and imprecision can be represented by possibility theory. The book reviews, extends and applies possibility theory in an integrated approach that combines probability theory, statistics and fuzzy mathematics.