
AbstractUncertainty is generally defined as ‘that which is not precisely known’. This definition permits the identification of different kinds of uncertainty arising from different sources and activities, most of which go unnoticed in analysis. In this paper, the evolution of uncertainty through time begins from a historical perspective and concludes with a new perspective based upon making inferences. The evolution of uncertainty, in terms of analytical progress, begins with assessing probabilities and concludes with models and methods for assessing the ‘total uncertainty’ within an application. Both evolutionary tracks are briefly described in the context of physical science and engineering applications; however, nothing presented precludes application to other fields, e.g. economics, social sciences, medicine and business. As we honor his 90th birthday, Zadeh’s fuzzy sets and logic play a prominent role in both evolutions. Uncertainty assessment involves how to identify, classify, characterize, quantify, and combine uncertainties within an application, with the expressed goal of understanding how to manage uncertainties. Managing uncertainties is important, because uncertainties directly affect decision and policy making. Assessment and quantification of uncertainties are generally defined and outlined. Mathematical developments are not provided and in some cases are still under or in need of development.
Fuzzy sets, Inference, Total uncertainty, Confidence, Uncertainty quantification
Fuzzy sets, Inference, Total uncertainty, Confidence, Uncertainty quantification
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 34 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
