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. Consequently, set theory and logic have been extended to deal with uncertainty. Possibility theory is the "umbrella" under which all forms of uncertainty can be suitably represented. This text provides an up-to-date introduction to possibility theory, describing it as an integrated approach that combines probability theory, statistics and fuzzy mathematics. It offers an integrated view on uncertainty techniques based on multi-valued mappings and fuzzy relations. Concepts are adopted into a temporal environment characterized by signal or data processing. Examples are taken from the area of condition monitoring to illustrate the application of possibility theory to data analysis in process and supervisory control systems.
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