Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)
Support Vector Machines: Theory and Applications (Studies in Fuzziness and Soft Computing)
Typhoon track prediction by a support vector machine using data reduction methods
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
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To solve imbalance problem of datasets in thunderstorm forecast, this paper introduced the concept of data field and proposed a resampling method based on potential value which is combined with the weighted Support Vector Machine[12-14] (SVM) to set up a new thunderstorm forecast model. Moreover we assessed the forecast model with a comprehensive assessment method based on imbalance measure and meteorological score. The experimental results showed that the model effectively controlled the adverse impact of unbalanced datasets to thunderstorm forecast. By the assessment of comprehensive assessment method, the results proved that the model is not only effective in dealing with the imbalance datasets, but also more practical in weather forecast.