TY - JOUR
T1 - A case-based reasoning approach to the identification of materials from diffraction patterns
AU - Kimmel, Giora
AU - HaCohen-Kerner, Yaakov
AU - Nissan, Ephraim
AU - Berman, Eugen
PY - 2009/3
Y1 - 2009/3
N2 - X-ray diffractometry, within materials engineering, is a promising area of application for case-based reasoning. A large database of spectral diffraction patterns includes entries with different quality marks; moreover, several diffraction patterns happen to be equivalent, identifying the same material (crystalline phase), even though it also happens, that a spectral diffraction pattern alone would not identify a crystalline phase, and parameters such as density also have to be involved for identification. Current practice in the scanning and processing of so-called powder diffraction files, out of a database of files (formerly cards), calls for improvements of various kinds. Arguably, case-based reasoning is a technique from within AI that appears to exhibit a very interesting potential to make the process of identification less cumbersome.
AB - X-ray diffractometry, within materials engineering, is a promising area of application for case-based reasoning. A large database of spectral diffraction patterns includes entries with different quality marks; moreover, several diffraction patterns happen to be equivalent, identifying the same material (crystalline phase), even though it also happens, that a spectral diffraction pattern alone would not identify a crystalline phase, and parameters such as density also have to be involved for identification. Current practice in the scanning and processing of so-called powder diffraction files, out of a database of files (formerly cards), calls for improvements of various kinds. Arguably, case-based reasoning is a technique from within AI that appears to exhibit a very interesting potential to make the process of identification less cumbersome.
UR - http://www.scopus.com/inward/record.url?scp=62149137620&partnerID=8YFLogxK
U2 - 10.1080/08839510802700185
DO - 10.1080/08839510802700185
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AN - SCOPUS:62149137620
SN - 0883-9514
VL - 23
SP - 282
EP - 295
JO - Applied Artificial Intelligence
JF - Applied Artificial Intelligence
IS - 3
ER -