Application of RS-SVM model for fire identification
Yang Liu · Computer Engineering and Applications Journal · 2010
An arithmetic for fire identification is proposed based on composite of Rough Set Support Vector Machine(RS-SVM). Firstly,using Rough Set theory,the six variables of fire characteristics mapped to the RS knowledge system are made,the redundant information is eliminated,the properties of the system are reduced,then the regulations of this knowledge system are acquired.By the generalization and nonlinear approach ability of SVM,the model using the regulations of this knowledge system is trained,ultimately,the accuracy and optimized fire identification algorithms are obtained.The simulation result indicates that the method has better performance of fire identification accuracy,converge speed,nonlinear approaching and immunity.