Record Display for the EPA National Library Catalog


OLS Field Name OLS Field Data
Main Title Classification of Binary Mass Spectra of Toxic Compounds with an Inductive Expert System and Comparison with SIMCA Class Modeling (Journal Version).
Author Scott, D. R. ;
CORP Author Environmental Monitoring Systems Lab., Research Triangle Park, NC.
Publisher 1988
Year Published 1988
Report Number EPA/600/J-88/254;
Stock Number PB89-143762
Additional Subjects Mass spectroscopy ; Information systems ; Environmental surveys ; Hazardous materials ; Chemical analysis ; Performance evaluation ; Pattern recognition ; Benzenes ; Alkanes ; Alkene compounds ; Chlorine organic compounds ; Bromine organic compounds ; Comparison ; Reprints ; Volatile organic compounds ; SIMCA models ; Environmental monitoring ; Expert systems
Library Call Number Additional Info Location Last
NTIS  PB89-143762 Most EPA libraries have a fiche copy filed under the call number shown. Check with individual libraries about paper copy. NTIS 06/08/1989
Collation 21p
The performance of an inexpensive, inductive rule-building expert system, 1ST CLASS, using the ID3 algorithm was compared to that of SIMCA class modeling in classifying the binary mass spectra of 78 toxic and related compounds. The compressed mass spectra consisted of 17 masses chosen using information theory. The expert rules verified the six main classes and two subclasses found with SIMCA class modeling. These classes were: all benzenes and all alkanes/alkenes (alkaenes); nonhalobenzenes, chlorobenzenes, bromoalkaenes, and chloroalkaenes; and mono-, dichloroalkaenes and polychloroalkaenes. Training set classification accuracies obtained with the expert rules gave a classification accuracy of 97-100% vs. 79-96% for SIMCA. Predictive accuracy for the four main classes was 78%. In general fewer masses were involved with the rules than with the SIMCA models, and the rules are normally optimized with regard to minimum number of steps in the rule, not minimum number of variables. The expert rules work best with closed sets of objects where all possibilities can be included in the training sets. The expert rules can be taken to be specified paths along the perimeter of the multidimensional measurement space (hypercube) to a vertex nearest the SIMCA cylinders for an appropriate class. Overall the performance of the expert system was very good.