A General Mathematical Approach Based on the Possibility Theory for Handling Measurement Results and All Uncertainties
| Autor: | Simona Salicone, Harsha Vardhana Jetti |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science Probabilistic logic Probability density function Lexical definition Machine learning computer.software_genre Expression (mathematics) Measurement uncertainty General Materials Science Artificial intelligence business computer Value (mathematics) Word (computer architecture) Possibility theory |
| Zdroj: | Metrology. 1:76-92 |
| ISSN: | 2673-8244 |
| Popis: | The concept of measurement uncertainty was introduced in the 1990s by the “Guide to the expression of uncertainty in measurement”, known as GUM. The word uncertainty has a lexical meaning and reflects the lack of exact knowledge or lack of complete knowledge about the value of the measurand. Thanks to the suggestions in the GUM and following the mathematical probabilistic approaches therein proposed, an uncertainty value can be found and be associated to the measured value. In the last decades, however, other methods have been proposed in the literature, which try to encompass the definitions of the GUM, thus overcoming its limitations. Some of these methods are based on the possibility theory, such as the one known as the RFV method. The aim of this paper is to briefly recall the RFV method, starting from the very beginning and the initial motivations, and summarize in a unique paper the most relevant obtained results. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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