Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system | IEEE Conference Publication | IEEE Xplore

Rainfall prediction in Tengger region Indonesia using Tsukamoto fuzzy inference system


Abstract:

Rainfall Prediction in Indonesia is very important for agricultural sector. However, obtaining an accurate prediction is difficult as there are too many input parameters ...Show More

Abstract:

Rainfall Prediction in Indonesia is very important for agricultural sector. However, obtaining an accurate prediction is difficult as there are too many input parameters including the world climate change that affect the accuracy. An accurate prediction is required to arrange a good schedule for planting agricultural commodities. A good approach is required to obtain a good model as well as the accurate prediction. This paper proposes Tsukamoto fuzzy inference system (FIS) to solve the problem. An intensive effort is put in building fuzzy membership function based on rainfall data in Tengger region from ten years ago. A series of numerical experiments prove that the proposed approach produces better results comparable to those achieved by other approach. In Tutur region Tsukamoto fuzzy inference system obtain Root Mean Square Error (RMSE) of 8.64, it is better than GSTAR-SUR method that obtain RMSE of 10.89.
Date of Conference: 23-24 August 2016
Date Added to IEEE Xplore: 02 January 2017
ISBN Information:
Conference Location: Yogyakarta, Indonesia

References

References is not available for this document.