September 19, 2025Advance Sustainable Science Engineering and TechnologyOpen Access

A Comparative Analysis of Time-Series Models of ARIMA and Prophet IoT-Based Flood Forecasting in Sungai Melaka

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Prophet model achieved a lower MAPE of 6% and RMSE of 5 in flood prediction, outperforming ARIMA.
IoT-driven flood forecasting utilized sensor data from an observatory system for model training and evaluation.
The performance analysis highlighted Prophet's superior accuracy, adaptability, and seasonality handling for flood forecasting.
Integrating environmental factors may enhance predictive accuracy by addressing Prophet’s limitations in abrupt water level changes.

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Implication

This analysis demonstrates Prophet outperforms ARIMA in flood prediction accuracy using IoT data, indicating potential for enhanced urban disaster management.

Cite This Study

Esro et al. (2025) studied this question.

synapsesocial.com/papers/68d43706713b0b5dfea76dda https://doi.org/10.26877/asset.v7i4.1048

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Implication

This analysis demonstrates Prophet outperforms ARIMA in flood prediction accuracy using IoT data, indicating potential for enhanced urban disaster management.

A Comparative Analysis of Time-Series Models of ARIMA and Prophet IoT-Based Flood Forecasting in Sungai Melaka

Key Points

Discussion

Implication

Cite This Study

A Comparative Analysis of Time-Series Models of ARIMA and Prophet IoT-Based Flood Forecasting in Sungai Melaka

Key Points

Discussion

Implication

Cite This Study