Fuzzy Rough Monotone Data Mining Algorithm With It’s Application Research In Wastewater Treatment

With more and more complexity of society development, data mining becomes an era research topic because of the complexity and the magnitude of information, so many data mining methods appear, and fuzzy and rough methods are two important tools for data mining. Rough sets acts as the data mining function mainly through the attributes reduction, but because the base of its mathematic is equivalent relationship, so there is much limit in many applications, then some people present some extensive relationship around the equivalent relationship such as consistent relationship, adjacent relationship, dominance relationship, and fuzzy equivalent relationship etc, at the same time many people present many attributes reduction algorithms. But because of the limit of these relationships, there always exist some problems in those attributes reduction algorithms based on them for application such as data inconsistent, the disperse of continuum data, data imperfect etc. Here this paper presents an idea that the world is fuzzy monotone after analyzing some phenomenon and the limit of current monotone definition in math, and then presents fuzzy rough monotone concept with relationship and some mathematic models combining with fuzzy and rough methods. Then some definitions of fuzzy monotone relationship and rough property are discussed, and the relationship is pointed out among fuzzy monotone relationship, equivalence relationship and current mathematic monotone relationship, then some rough properties are developed in fuzzy monotone relationship. Some data mining methods are presented based on advance zone partition methods method and fuzzy rough monotone model, which is through adopting the order and map theory. After the experiment, effects of these algorithms are validated and their merit is shown through the comparisons with other attributes reduction algorithms. At last fuzzy rough monotone method are combined using with neural networks. Innovative points in this paper are as follows:(1) Fuzzy rough monotone relationship and concept are presented and defined; four fuzzy monotone mathematic models and the rough definition of fuzzy monotone models are presented according to rough theory. The relationship among fuzzy monotone relationship, equivalent relationship and normal monotone relationship is discussed and analyzed; some rough properties of fuzzy monotone models are developed according to the rough theory.(2) A zone partition method is presented according to the order and map theory based on decision table and fuzzy monotone models; two fuzzy monotone membership functions are presented based on minimum and average value of zone separately; two fuzzy monotone relationships are constructed and their parameters properties are discussed after some propositions are presented and proved; then two data mining algorithms based on minimum and average value of zone separately are presented; the UCI international wastewater data are used to validate the effect of two data mining algorithms after the decision rules being analyzed and designed; the rough and fine degree of these two data mining algorithms is compared and analyzed; the merits and different properties are shown thorough the comparison of other attributes reduction algorithms, and the time complexity is given too.(3) Fuzzy inclusive monotone concept is introduced into decision table according to inclusion theory and fuzzy monotone model methods based on fuzzy monotoneâ…£model; the fuzzy inclusive monotone relationship between input condition attributes and output decision attributes is constructed after some propositions are presented and proved; the fuzzy inclusive monotone decision membership function is deduced; the fuzzy rough monotone data mining algorithm based inclusion degree is presented based on the membership function; the different properties and the effect of the algorithm is shown by the comparison of above two algorithms; the merit of the algorithm is shown by the comparison of other attributes reduction and those based on inclusion degree too;(4) A pretreatment model of wastewater dissolved oxygen based on RBF neural networks is presented through the analysis of wastewater dissolved oxygen control model; the model is effective in certain extension and exists some problems after the validation of the data of a guangzhou wastewater treatment factory combined with evolutionary optimized method, then a fuzzy rough monotone RBF neural networks forecast model is presented and its effect is validated by UCI wastewater data ,and some problems for former model method are improved in latter model method; then a fuzzy rough pretreatment model of wastewater dissolved oxygen based on RBF neural networks is presented, which is combined using fuzzy rough monotone method and neural networks method.