Knowledge Acquisition for Reconstruction and Identification of Dimensionless Groups by Means of Case Based Reasoning

4 Pages Posted: 31 Dec 2019

Date Written: December 10, 2019

Abstract

When searching with Data Mining Techniques to identify or find out dimensionless groups (DGs) in technical literature, it is possible to meet errors/faults/omissions concerning both, the form and the content of such groups. In the present study, a methodological framework has been developed in terms of a logical flow chart, including 11 activity stages and 7 decision nodes, to acquire/process/store/retrieve knowledge for reconstruction and identification of these groups. Case Based Reasoning (CBR), especially modified to meet the needs of this work, has been used for tracing causality paths by similarity and making correction suggestions. Two case examples are presented to prove the functionality of the proposed methodology.

Keywords: dimensional analysis, knowledge acquisition, dimensionless groups, case based reasoning, data mining, Blake number, modified Reynolds number, adsorption, sedimentation, flocculation, filtration, scale up

Suggested Citation

Batzias, Fragiskos A. and Kopsidas, Odysseas, Knowledge Acquisition for Reconstruction and Identification of Dimensionless Groups by Means of Case Based Reasoning (December 10, 2019). Available at SSRN: https://ssrn.com/abstract=3501392 or http://dx.doi.org/10.2139/ssrn.3501392

Fragiskos A. Batzias

University of Piraeus

Karaoli and Dimitriou 80
80 KARAOLI & DIMITRIOU STREET
Piraeus, Attiki 18534
Greece

Odysseas Kopsidas (Contact Author)

University of Piraeus ( email )

80 Karaoli & Dimitriou str.
Piraeus, 18534
Greece

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