Severe Convection Weather Identification Model Based on Rough Set Theory and Artificial Fish Swarm Algorithm

In order to solve the problem of identifying severe convection weather, this paper proposes a model of identifying severe convection weather based on rough set theory and artificial fish swarm algorithm. First, based on the radar reflectivity images, the echo attributes of the severe convection area are analyzed and extracted. Second, this paper proposes a discretization method based on rough set theory. This method discretizes the meteorological data and establishes a decision table. Third, the improved artificial fish swarm algorithm is used to reduce attributes and obtain the minimum attribute set. Finally, the classification and regression tree (CART) algorithm and the cost-complexity pruning (CCP) principle are used to establish an objective model for identifying severe convection weather. Experimental results show that the model in this paper can recognize severe convection weather under the condition of a few attributes and the identification model has high accuracy.