Spectrum interpretation knowledge-based systems

Many expert systems contain a knowledge base in the form of a decision tree that is constructed from a series of decision nodes connected by branches. For instance, in expert systems developed for the interpretation of vibrational spectra, decision trees are typically used in a sequential manner. Similar to the interpretation of a spectrum... 

The logical approach was u,sed for creating computer systems for the structural interpretation of the IR spectrum, the T(A, 2) function being presented by the system s knowledge base. A description of the systems based on logical rules can be found in reviews and the original publications. 5 ... 

A database containing the codified knowledge of an expert. It is used as a basis for the intelligent behavior of artificial intelligence systems. The knowledge is compiled by experts or is extracted in a process of knowledge acquisition. It is a central part of expert systems. See Structure Determination by Computer-based Spectrum Interpretation and Synthesis Design. 

Agapito et al. ° applied fuzzy logic to an array of semiconductor gas sensors to analyze different atmospheres for the different gases and Otto et al. developed a scheme based on the principles of fuzzy logic that makes use of various pieces of information available either from spectroscopic knowledge or from the particular spectrum that requires evaluation. A fuzzy expert system has also been successfully developed for the automated qualitative and semiquantitative interpretation of X-ray diffraction spectra/ automation of matrix-assisted laser desorption-ionization mass spectrometry (MALDI), and for polymer analysis. 

Although the above equations imply that a lot of symmetry analyses must be performed, that is not always the case. Equations 14.2 and 14.3 allow for the possibility of broad statements about which transitions will and will not be allowed for particular atomic or molecular systems. Such general statements, ultimately based on quantum mechanics and symmetry, are called selection rules. Selection rules allow us to easily determine which transitions will occur. When one is faced with a spectrum to interpret, knowledge of the selection rules is an indispensable tool in deriving physical information from the spectrum. Rotational and vibrational spectroscopy, in this chapter, are simplified to a large extent thanks to selection rules. 

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