Cumulonimbus forecasting based on rough set and artificial immune algorithm

Some small scale weather, such as thunderstorm or cumulonimbus, is a grave threat to civil aviation flight safety. In despite of a great deal of data having been accumulated these years, the civil weather departments still primarily use traditional meteorology methods, mainly by the subjective factors of forecasters, to predict weather occurrence, development and changes. Data of Haikou and nearby cities are prepared firstly, then data discretization, attribute reduction and rule extraction based on rough set theory are used to analyze weather data. Because of serious imbalance phenomenon of the data and based on the rule classification, artificial immune classifier is used to deal with the problem on data recognition, finally we present a cumulonimbus forecasting model based on rough set and artificial immune algorithm which is proved effective by experimental results.