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Monthly Runoff Prediction by Support Vector Machine Based on Whale Optimisation Algorithm

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Intelligent System Design

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 494))

Abstract

This study was conducted in catchment area of Baitarani River at Jaraikela, situated in Eastern India. The Baitarani River is one of the most important rivers in the eastern region of peninsular India, which later joins the Bay of Bengal. This region frequently experiences floods due to its erratic rainfall patterns and climatic conditions, which makes runoff prediction important for planning better watershed management techniques and mitigation strategies. To simulate rainfall-runoff process, SVM model integrated with Whale Optimisation Algorithm (WOA) method has been used. WOA enhances the results by reducing the error margin in SVM. For this purpose, 48 years (1981–2020) of statistical data have been used for calibration, validation and testing of the model. The results show that the hybrid SVM-WOA model outperforms the classical SVM model in terms of forecasting accuracy and efficiency based on root mean squared error (RMSE), mean absolute error (MAE), and Nash–Sutcliffe efficiency (NE) performance evaluation measures.

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Author information

Authors and Affiliations

  1. Department of Civil Engineering, OUTR Bhubaneswar, Bhubaneswar, Odisha, India

    Aiswarya Mishra, Sandeep Samantaray & Deba Prakash Satapathy

  2. Department of Civil Engineering, NIT Silchar, Silchar, Assam, India

    Abinash Sahoo

  3. Department of Computer Science and Engineering, KIIT University, Bhubaneswar, Odisha, India

    Suresh Chandra Satapathy

Authors
  1. Aiswarya Mishra
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  2. Abinash Sahoo
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  3. Sandeep Samantaray
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  4. Deba Prakash Satapathy
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  5. Suresh Chandra Satapathy
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Corresponding author

Correspondence to Sandeep Samantaray .

Editor information

Editors and Affiliations

  1. Dr. A.P.J. Abdul Kalam Technical University, Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial College of Engineering and Management (SRMCEM), Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  2. Principal, BVRIT Hyd. College of Engineering for Women, Hyderabad, Telangana, India

    K. V. N. Sunitha

  3. College of Information Science and Eng, Ritsumeikan University, Kusuatsu, Shiga, Japan

    Yen-Wei Chen

  4. Department of Informatics, University of Leicester, Leicester, UK

    Yu-Dong Zhang

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Cite this paper

Mishra, A., Sahoo, A., Samantaray, S., Satapathy, D.P., Satapathy, S.C. (2023). Monthly Runoff Prediction by Support Vector Machine Based on Whale Optimisation Algorithm. In: Bhateja, V., Sunitha, K.V.N., Chen, YW., Zhang, YD. (eds) Intelligent System Design. Lecture Notes in Networks and Systems, vol 494. Springer, Singapore. https://doi.org/10.1007/978-981-19-4863-3_31

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