Excessive rainfall is one of the triggers for the flooding phenomenon, especially in the tropics with flat or concave areas. Some critical points in the South Tangerang region, which are currently one of the most rapidly developing cities, cannot be ignored from the flooding problem. Floods cause disturbing human activities, loss of life and property, and in turn affect the economic stretch in an area. This work aimed to predict rainfall by exploring the application of artificial intelligence techniques such as Support Vector Machine, Deep Neural Network, ANFIS (Adaptive NeuroFuzzy Inference System). The SVM, Deep NN & ANFIS model with various input structures was built, trained, and tested to evaluate the capability of a model. Analyses of 115-year (1901-2015) rainfall data on a monthly basis in India, found that rainfall prediction based on ANFIS time series is promising where 99.8% of data testing is well predicted.
MATLAB file for this work is available at the following link: