Rain Prediction using Fuzzy Logic
Manish Kumar Singla1, Harkamal Deep Kaur2, Parag Nijhawan3

1Manish Kumar Singla, EIE Department, Thapar Institute of Engineering and Technology.
2Harkamal Deep Kaur, EIE Department, Thapar Institute of Engineering and Technology.
3Parag Nijhawan EIE Department, Thapar Institute of Engineering and Technology, Patiala (INDIA).
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2796-2799| Volume-9 Issue-1, October 2019 | Retrieval Number: A9781109119/2019©BEIESP | DOI: 10.35940/ijeat.A9781.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Power system energy management system is observed as the breakthrough element for load forecasting. Load forecasting is advantageous so as to reduce the generation cost, spinning reserve capacity and increase the reliability of power system. The unit commitment, economic allotment of generation preservation schedule is crucial for short term load forecasting (STLF). In the current times, many techniques are being utilized for load forecasting, but Artificial Intelligence Technique (Fuzzy Logic and ANN) provides improved efficiency as in contrast with conventional technique (Regression and Time Series). In this particular paper, the author main purpose is to reduce flood conditions and drought. The main focus of the author is in the prediction of rainfall with the help of wind variation and temperature, speed. The paper represents a technique of STLF using fuzzy logic. Using Mamdani implication the fuzzy rule base is prepared. The software used for this is Matlab Simulink and fuzzy tool box. By using triangular membership function the forecasted results are obtained.
Keywords: Fuzzy logic, Fuzzy interface system, Mamdani, STLF.