Max-Min classification model for rough data
Fachao Li · Journal of Tsinghua University(Science and Technology) · 2004
Evolutionary computational methods play an important role in many practical problems such as production line optimization in complex manufacturing systems with uncertain environments. This paper reviews the current development of evolutionary computational methods and the short comings of fuzzy information processing. A Max-Min classification model for rough data was then developed with two basic parameters, a classification parameter and an adjustment parameter for the classification. The Max-Min classification model is shown to be a proportional classification model for sufficiently large classification parameters. Therefore, the Max-Min classification model is a more extensive classification method compared to the common proportional classification method, which makes the Min-Max method better for uncertain information than current classification methods which are not fit for rough data. The Min-Max model includes an evolutionary reproduction procedure for individuals in an under uncertainty environment.