Integrating Domain Knowledge with Data: From Crisp to Probabilistic and Fuzzy Knowledge
Hung Tan Nguyen, Владик Крейнович, Leon Reznik · scholarworks - UTEP (The University of Texas at El Paso) · 2000
It is well known that prior knowledge about the domain can improve (often drastically) the accuracy of the estimates of the physical quantities in comparison with the estimates which are solely based on the measurement results. In this paper, we show how a known method of integrating crisp domain knowledge with data can be (naturally) extended to the case when the domain knowledge is described in statistical or fuzzy terms. 1 INTEGRATING DOMAIN KNOWLEDGE WITH DATA: FORMULATION OF THE PROBLEM A large part of information about the world comes from measurements. However, for many complex systems, some characteristics are very difficult to measure: e.g., for a jet engine, it is difficult to measure the temperature and pressure inside the jet chamber, where the temperatures are very high; for a human body, it is difficult to measure the characteristics of the internal organs, etc. In many such cases, experts have some knowledge about the domain. It is therefore desirable to us...