Performance Analysis of Fuzzy Mamdani for Flood Mitigation Water Gate Control
DOI:
https://doi.org/10.32492/nucleus.v5i2.5215Keywords:
Mamdani Fuzzy Inference System, Flood Mitigation, Water Gate Control, Water Level MonitoringAbstract
Flood events continue to be a major natural disaster worldwide, resulting in significant losses to infrastructure, economic sectors, and public welfare. Effective flood mitigation requires adaptive water gate control systems capable of responding to dynamic hydrological conditions. This study evaluates the performance of a Mamdani Fuzzy Inference System (FIS) for flood mitigation water gate control using three input parameters: water level, rainfall intensity, and water flow rate. The proposed system was developed and simulated using the MATLAB Fuzzy Logic Toolbox. Triangular membership functions were applied to all input and output variables, while 27 fuzzy IF–THEN rules were designed to represent hydrological decision-making knowledge. A total of 20 simulation scenarios were conducted to assess the controller performance under various environmental conditions. The results show that the proposed Mamdani FIS can generate adaptive floodgate opening decisions ranging from closed and partially open to fully open positions according to the severity of hydrological conditions. Performance evaluation produced an RMSE of 1.0074, an MAE of 0.7050, and an accuracy of 98.99%, indicating reliable and consistent decision-making capability. Furthermore, surface analysis demonstrated smooth output transitions and stable controller behavior across different input combinations. These findings indicate that the proposed approach can effectively support intelligent floodgate operation and provide a promising solution for flood mitigation applications.
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