Rainfall Based Flood Prediction in Kerala Using Machine Learning

Authors

  • Vidya S Associate Professor, Sri Sai Ram Institute of Technology, Chennai, India
  • Gayathri S U.G. Student, Sri Sai Ram Institute of Technology, Chennai, India
  • Dilsha M U.G. Student, Sri Sai Ram Institute of Technology, Chennai, India
  • Krithika S U.G. Student, Sri Sai Ram Institute of Technology, Chennai, India

Keywords:

Deep Learning, Flood Prediction, Hydrological model, Machine Learning, Statistical analysis

Abstract

Among the most damaging natural disasters are floods, which are very difficult to model. Flood prediction is a critical task that involves forecasting the likelihood of floods in a given area, allowing people to take necessary precautions to minimise damages and prevent loss of life. Machine learning (ML) algorithms have shown great potential in flood prediction, as they can analyse large amounts of data from multiple sources to provide accurate and timely predictions. The objective is to find a prediction model that is more accurate and efficient by incorporating new machine learning techniques and hybridising current ones. Both hydrologists and climate scientists can use this model as a guidance for selecting the appropriate machine learning technique for a given prediction problem. The output of the ML-based flood prediction system can also be integrated with existing flood warning systems, enabling authorities to send out alerts in a timely manner and take necessary precautions to minimise the effects of flooding.

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References

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Published

23.02.2024

How to Cite

S, V. ., S, G. ., M, D. ., & S, K. . (2024). Rainfall Based Flood Prediction in Kerala Using Machine Learning. International Journal of Intelligent Systems and Applications in Engineering, 12(16s), 141–144. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4800

Issue

Vol. 12 No. 16s (2024)

Section

Research Article

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