Study Of Infrared Feature Of Oxygen-contained Compounds

An important trend of the development of technique is the informationization of science and techniques. Analytical chemistry, actually, is an information science of chemistry, and the chemometrics is the result of the informationization of analytical chemistry. Historically, the accumulated collection of the scientific data always results in the discovery of important scientific rules. This provides the opportunity to mine the data of chemometrics. With the bigger amount of the infrared spectra database, the deeper development of the infrared technology and of the computer, it is urgent to find a solution about how to utilize and enlarge the application of infrared spectra. In the past decades, people are trying to search the way to interpret the infrared spectra. Along with the computerization of the infrared spectrometry, many computer-assisted interpretations emerged. The automatic structure elucidation of infrared spectra generally falls into three groups: library search, knowledge-based systems, or pattern recognition. Among the last group, artificial neural networks (ANNs) and partial least squares (PLS) were most frequently used. Automatic interpretation of infrared spectra by using pattern recognition techniques such as artificial neural networks has dominant focus on substructure prediction. Absorption bands are ignored on classification. Furthermore, ANNs have several major drawbacks: unsteadiness, local minima and very low speed of convergence.In this paper, a new approach is established attempting to extract the structural information of the oxygen-contained compounds in different chemical surroundings...