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Abstract
A new method has been developed for the prediction of rainfall and its quantity at a place given its past record. The new method is being introduced and explained with an example to show how it works. Detailed algorithm is described in the paper. The prediction is made based on historic data using the fact that whether the certain weather conditions have caused rainfall or not in the past at the place. The model is at its early stage and uses only four parameters (Temperature, Atmospheric Pressure, Humidity and Rainfall). Several more parameters (weather conditions such as wind speed, etc) have to be taken into account to lead to reliable forecasting or rainfall prediction..
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References
- Rainfall prediction model using soft computing technique - K. W. Wong, P. M. Wong, T. D. Gedeon, C. C. Fung
- A Neuro-Fuzzy Approach for Daily Rainfall Prediction over the Central Region of Thailand - PramoteLuenam, SupawadeeIngsriswang, Lily Ingsrisawang, PrasertAungsuratana, and WarawutKhantiyanan
- Long Lead Rainfall Prediction Using Statistical Downscaling and Artificial Neural Network Modelin - M. Karamouz, M. Fallahi, S. Nazif and M. RahimiFarahani
- Rain rate and rain attenuation prediction for satellite communication in Ku and Ka bands over Nigeria. - J.S Ojo, M.O Ajewole, S.K Sarkar
References
Rainfall prediction model using soft computing technique - K. W. Wong, P. M. Wong, T. D. Gedeon, C. C. Fung
A Neuro-Fuzzy Approach for Daily Rainfall Prediction over the Central Region of Thailand - PramoteLuenam, SupawadeeIngsriswang, Lily Ingsrisawang, PrasertAungsuratana, and WarawutKhantiyanan
Long Lead Rainfall Prediction Using Statistical Downscaling and Artificial Neural Network Modelin - M. Karamouz, M. Fallahi, S. Nazif and M. RahimiFarahani
Rain rate and rain attenuation prediction for satellite communication in Ku and Ka bands over Nigeria. - J.S Ojo, M.O Ajewole, S.K Sarkar