Abstract The theory of fuzzy sets was applied to specific infrared spectrum-structure-correlations. The scheme was translated into a rule base named CorTab (from Correlation Tables). The data are split into three main data files consisting of the structural information, the spectral properties and the cross references. The first two files contain the fragments and the ranges of the spectroscopic features, i.e. position, intensity and band width, and also the empirical knowledge about the plausibility or constraints of the correlations. The cross references assign the spectral to the structural properties and contain the connections between the fragments in the network of the fragments. The flexibility of the design allows the ongoing accumulation of spectrum-structure-correlations from different literature sources or the storage of computer derived rules. The rule base CorTab is a prerequisite for the structure elucidation performed by an ensemble of interpretation systems relying on fuzzy logic. A survey of the arrangement and contents of the rule base and the procedures that transform the verbally given knowledge into linguistic – fuzzified – variables are reported herein.
[1]
G. Socrates,et al.
Infrared Characteristic Group Frequencies
,
1980
.
[2]
Hans-Jürgen Zimmermann,et al.
Fuzzy set theory
,
1992
.
[3]
Didier Dubois,et al.
Possibility Theory - An Approach to Computerized Processing of Uncertainty
,
1988
.
[4]
E. Pretsch.
Tabellen zur Strukturaufklärung organischer Verbindungen mit spektroskopischen Methoden
,
1976
.
[5]
S. Wiberley,et al.
Introduction to infrared and Raman spectroscopy
,
1965
.
[6]
D. Lin-Vien.
The Handbook of Infrared and Raman Characteristic Frequencies of Organic Molecules
,
1991
.
[7]
R. Gleiter.
E. Pretsch, T. Clerc, J. Seibl und W. Simon: Tabellen zur Strukturaufklärung organischer Verbindungen mit spektroskopischen Methoden. Springer Verlag, Berlin‐Heidelberg‐New York 1976. 312 S., Preis: DM 28,—.
,
1977
.
[8]
L. J. Bellamy.
The infra-red spectra of complex molecules
,
1962
.
[9]
Camilla Schwind,et al.
Schließen bei unsicherem Wissen in der Künstlichen Intelligenz
,
1992
.