Rules extracting of weather data based on rough set theory

In order to find rules of disaster weather from the history data and provide some support for the weather forecast, rough set theory was introduced into the field and a weather data model based on it was built. The model included the processes of data discretization, attributes reduction and rules extracting. For the rules extracting a new method based on discriminated matrix was proposed. The method made use of the fore-step, i.e., the attributes reductionpsilas computing results, so it reduced the algorithmpsilas time complexity of gaining the rules. And, it could get all reduction rules. Applied the method into the 30 yearpsilas weather data of Hebei province, the results proved that it was feasible and effective.