Applications Of Improved Attribute Recognition Methods To Water Environment System Assessment

Water as a special resource, which sustains all life, is the substance of sustainable development society. With the rapid development of economy and growth of population recently, Water environment quality becomes more and more acute. Water environment quality assessment is precondition work of improving water system function and its assessment result also is importance gist of constituting science decision-making. Firstly discuss the basic theory of attribute recognition methods and the study actuality and evolvement of water environment quality aptitude assessment methods. In allusion to difficulty of describing the complicated relation between the input and output data of water environment quality system assessment, present improment attribute recognition methods by accelerating genetic algorithm (AGA),set pairs (SP) theroy,minmum attribute relative information entropy (MARE). Finally give the applications of those improvement methods above to water environment quality assessment: (l)Using even random number makes sure single index weight , found assessment model based on attribute even clustering and apply to assessment in pollution degree of the city underwater. (2) combine set pairs (SP) idea, improve calculation modes of single index measure and apply to assessment in sewage treatment plant rebuilding and continuation. (3) construct attribute relative entropy between the assessment standard series and samples, found assessment model based on minmum attribute relative entropy(MARE) and apply to water quality asseaament in Wei River valley. It is concluded that these improvement models stated can be reliability and practicability.