Incomplete Information Systems, Rough Set Attribute Reduction Evolutionary Algorithm And Applied Research

Attributes reduction, the core of the Rough Set Theory, which is a new type of theory as the tool dealing with the uncertain knowledge, is the focal point of algorithm research for rough set. The minimum attributes reduction set is expected to acquire the brief regulated set. This is taken as NP-hard Problem, which can be figured out through the heuristic algorithm. With the purpose of knowledge acquisition as well as the view of rough set theory as its tool and the incomplete information systems as its objective, the attributes reduction algorithm and the application of the incomplete information systems are researched in the thesis based on rough set theory.Firstly, the attributes reduction algorithm is studied under the incomplete information systems. A new algorithm method is put forward based on tolerance relation as well as using Genetic Algorithm to acquire the assignment reduction, and the effectiveness is illustrated by an example analyzing. Through this research, the goal to develop the application range of the data mining under the incomplete information system has been achieved. Meanwhile, the new algorithm provides the rough set algorithm with a new research orientation.Secondly, a knowledge acquisition model for the incomplete information systems for the university personnel system on the basis of the tolerance relation assignment reduction using GA is designed. According to it, a new decision-making approach can be provided to improve the personnel management's efficiency as well as make the management more scientific and purpose-oriented in the new environment at universities. The model, which tends to solve the brain- drainning problems, can be both widely used and expanded.