Purnomo, Rosyana Fitria and Ramaputra, M. Galih and Herwanto, Riko (2018) RAINFALL PREDICTION WITH TSUKAMOTO FUZZY INFERENCE SYSTEM. RAINFALL PREDICTION WITH TSUKAMOTO FUZZY INFERENCE SYSTEM.
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Abstract
Rainfall Prediction in Indonesia is very important for the agricultural sector. However, getting accurate predictions is difficult because there are too many input parameters including global climate change that affect their accuracy. Study of weather prediction is a challenge that is always interesting to study. Although there was several methods of weather prediction, but the results have not provided good accuracy. The use of fuzzy logic has been proven by scientists to be applied to the expression of uncertainty, it is not clear and qualitative from a system. A prediction is needed to set a good schedule for planting agricultural commodities. The reliability of this prediction depends on accuracy in choosing correlated variables. If existing historical databases fail to record the most correlated variables, then the reliability of these data-driven forecast approaches is questionable. This paper proposes Tsukamoto fuzzy inference system (FIS) to simulate problem solving. Intensive efforts were made to build a fuzzy membership function based on rainfall data in the South Lampung region from ten years ago. Some numerical experiments prove that the proposed approach produces better than that achieved by other approaches. Keywords - Prediction, Rainfall, Tsukamoto Fuzzy Inference System, South Lampung
| Item Type: | Article |
|---|---|
| Subjects: | Ilmu Komputer |
| Divisions: | Artikel Ilmiah Dosen > Fakultas Ilmu Komputer |
| Depositing User: | mr R H |
| Date Deposited: | 02 Sep 2019 02:20 |
| Last Modified: | 02 Jul 2021 03:11 |
| URI: | http://repo.darmajaya.ac.id/id/eprint/232 |
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