Novel computer-assisted interpretation method to recognize saturated alkane with the help of data mining

Based on the discovering and summarizing of several new concrete rules of alkanes mass spectra, a novel method for recognizing alkanes was proposed in the style of stepwise question and answer by applying data mining technique in Nist107 database of mass spectra of standard compounds. Two experiments were designed by implementing the presented scheme deliberately, and satisfactory results appeared in those tests. In the former test, the occurrence percentage of type I errors is 0.503% while the counterpart of type II errors is 0.008%. Meanwhile, the normal alkane could be perfectly recognized by this method. In the later test, a component, whose spectrum is a result of HELP resolution, is accurately determined as n-C-11 H-24 from candidates gained utilizing dot-product similarity algorithm. This technique could be used to recognize and determine alkane in fast detection of essential oil in plant, PONA analysis and solid particulate matter in the air. The presented approach is programmed by MatLab6.5.