Journal of Environment Protection and Sustainable Development
Articles Information
Journal of Environment Protection and Sustainable Development, Vol.5, No.2, Jun. 2019, Pub. Date: May 22, 2019
A Study on Rainfall Calibration and Estimation at the Northern Part of Bangladesh by Using Mamdani Fuzzy Inference System
Pages: 58-69 Views: 179 Downloads: 69
[01] Ahammodullah Hasan, Department of Mathematics, Faculty of Science, Islamic University, Kushtia, Bangladesh.
[02] Mohammad Anisur Rahman, Department of Mathematics, Faculty of Science, Islamic University, Kushtia, Bangladesh.
In this paper, the Mamdani fuzzy inference system has been used to estimate the average rainfall behaviour in the north part of Bangladesh. The authorized rainfall data of Bangladesh Meteorological Department were calibrated for better estimation. To perform the fuzzy inference system, knowledge base and the fuzzy reasoning or decision making functional components were used. The mn rules of fuzzy-logic principles were used to make operations for both the cases of fuzzification operation and defuzzification operation. The triangular membership functions were used for three major parameters (Temperature, Humidity, Wind speed) of Environment. In addition, the input and output variables were initially partitioned into five linguistic ranges Very high, High, Medium, Low, and Very Low. The developed system was then applied to the calibrated data to find the actual estimation. In this study, we have found the observed data and the estimated result makes a good agreement. The developed fuzzy rule-based model shows flexibility and ability in modelling an ill-defined relationship between input and output variables. The model estimation error was found below the 5% significance level. The RMS value of the estimated result was 0.51%. The study of fuzzy logic based rainfall prediction method by using the Mamdani fuzzy inference system may be successively used for different environmental problem estimation to mitigate unexpected meteorological problems.
Fuzzy Logic, Membership Function, Rainfall Estimation, Rules-Based, FIS, Fuzzy Levels, Fuzzification, Defuzzification
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