การพัฒนาแบบจำลองสำหรับคาดการณ์ปริมาณน้ำท่าบริเวณลุ่มน้ำมูล

วารสารวิชาการและวิจัย มทร.พระนคร, 11 (2) : 37-47In this paper proposed remote sensing using Normalized Difference Vegetation Index from NOAA STAR, cluster value from k-means, temperature, rainfall, number of rainy days and runoff to create runoff prediction model using Artificial Neural Network (ANN) and evaluated runoff models with the R2 and RMSE. The results show that the using of cluster value with other parameters to create predictive models can enhance forecasting results. When using Normalized Difference Vegetation Index with temperature value at lag time 1-2 month and cluster value at lag time 1 month to create model with ANN, we have got the best performance which are RMSE=0.09 and R2=0.743. The experimental results shows that remote sensing data and cluster value from k-means can be used to predictive the runoff effectively.Rajamangala University of Technology Phra Nakho