Fog Forecast Method Based on SVM and Model Identification
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Abstract:
By means of Support Vector Machine (SVM) and nine meteorological element data near the surface layer before heavy fog occurring in December and November from 1971 to 2000 (air temperature, precipitation, visibility, wind speed, wind direction, relative humidity, and overall and low cloud cover), a 24hour heavy fog forecast model for the highway in Shaanxi Province is developed. The model, based on the Gauss kernel function, has put to trial use and gets satisfactory TS scores through simulating and training in fog forecasting.