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University of Texas at El Paso

Expert knowledge

Publication Year

Articles 1 - 4 of 4

Full-Text Articles in Computer Engineering

Fuzzy (And Interval) Techniques In The Age Of Big Data: An Overview With Applications To Environmental Science, Geosciences, Engineering, And Medicine, Vladik Kreinovich, Rujira Ouncharoen Jan 2015

Fuzzy (And Interval) Techniques In The Age Of Big Data: An Overview With Applications To Environmental Science, Geosciences, Engineering, And Medicine, Vladik Kreinovich, Rujira Ouncharoen

Departmental Technical Reports (CS)

In some practical situations -- e.g., when treating a new illness -- we do not have enough data to make valid statistical conclusions. In such situations, it is necessary to use expert knowledge -- and thus, it is beneficial to use fuzzy techniques that were specifically designed to process such knowledge. At first glance, it may seem that in situations when we have large amounts of data, the relative importance of expert knowledge should decrease. However, somewhat surprisingly, it turns out that expert knowledge is still very useful in the current age of big data. In this paper, we explain how exactly ...


Using Expert Knowledge In Solving The Seismic Inverse Problem, Matthew G. Averill, Kate Miller, George R. Keller, Vladik Kreinovich, Roberto Araiza, Scott A. Starks Mar 2006

Using Expert Knowledge In Solving The Seismic Inverse Problem, Matthew G. Averill, Kate Miller, George R. Keller, Vladik Kreinovich, Roberto Araiza, Scott A. Starks

Departmental Technical Reports (CS)

For many practical applications, it it important to solve the seismic inverse problem, i.e., to measure seismic travel times and reconstruct velocities at different depths from this data. The existing algorithms for solving the seismic inverse problem often take too long and/or produce un-physical results -- because they do not take into account the knowledge of geophysicist experts. In this paper, we analyze how expert knowledge can be used in solving the seismic inverse problem.


On Efficient Representation Of Expert Knowledge By Fuzzy Logic: Towards An Optimal Combination Of Granularity And Higher-Order Approaches, Hung T. Nguyen, Vladik Kreinovich Apr 2002

On Efficient Representation Of Expert Knowledge By Fuzzy Logic: Towards An Optimal Combination Of Granularity And Higher-Order Approaches, Hung T. Nguyen, Vladik Kreinovich

Departmental Technical Reports (CS)

A natural approach to designing an intelligent system is to incorporate expert knowledge into this system. One of the main approaches to translating this knowledge into computer-understandable terms is the approach of fuzzy logic. It has led to many successful applications, but in several aspects, the resulting computer representation is somewhat different from the original expert meaning. Two related approaches have been used to make fuzzy logic more adequate in representing expert reasoning: granularity and higher-order approaches. Each approach is successful in some applications where the other approach did not succeed so well; it is therefore desirable to combine these ...


Optimal Elimination Of Inconsistency In Expert Knowledge: Formulation Of The Problem, Fast Algorithms, Timothy J. Ross, Berlin Wu, Vladik Kreinovich Sep 2000

Optimal Elimination Of Inconsistency In Expert Knowledge: Formulation Of The Problem, Fast Algorithms, Timothy J. Ross, Berlin Wu, Vladik Kreinovich

Departmental Technical Reports (CS)

Expert knowledge is sometimes inconsistent. In this paper, we describe the problem of eliminating this inconsistency as an optimization problem, and present fast algorithms for solving this problem.