Sensor data fusion technology is widely employed in fault diagnosis. The information in a sensor data fusion system is characterized by not only fuzziness, but also partial reliability. Uncertain information of sensors, including randomness, fuzziness, etc., has been extensively studied recently. However, the reliability of a sensor is often overlooked or cannot be analyzed adequately. A Z-numb...

In previous papers, the consequences of the "presence of fuzziness" in the experimental information on which statistical inferences are based were discussed. Thus, the intuitive assertion ((fuzziness entails a loss of information)) was formalized, by comparing the information in the "exact case" with that in the "fuzzy case". This comparison was carried out through different criteria to compare...

Measurement results contain different kinds of uncertainty. Besides systematic errors andrandom errors individual measurement results are also subject to another type of uncertainty,so-called emph{fuzziness}. It turns out that special fuzzy subsets of the set of real numbers $RR$are useful to model fuzziness of measurement results. These fuzzy subsets $x^*$ are called emph{fuzzy numbers}. The m...

Imperfect knowledge of the world is one of the main issues AI systems have to deal with. In recent years there has been much interest in coping with such imperfections in planning systems. However, most works only emphasize one side of the problem, namely uncertainty. We argue that vagueness (or imprecision) is a fundamental issue which planning systems should also take into account. With this ...

The paper brings a discussion about the source of the inaccuracy in observations of objects and demonstrates that the essential reason of the lack of precision is changeability, and the more changeability, i.e. more dynamics, can be experienced the more inaccurate, more fuzzy judges can be. The space of ordered fuzzy numbers (OFN), the new model of fuzzy numbers that make possible to deal with ...