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Application of a Combined GRNN-FOA Model for Monthly Rainfall Forecasting in Northern Odisha, India

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Intelligent System Design

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

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Abstract

Rainfall forecasting is considered the most complex variable in the hydrological cycle, and often its cause-impact relationship cannot be articulated in complex or simple mathematical terms. Because of climate change, the varying amount of rain can lead to either surplus or dryness in reservoirs. This research introduces a novel hybrid model generalised regression neural network integrated with fruit fly optimisation algorithm (GRNN-FOA), to forecast monthly rainfall. Rainfall data were collected from a local meteorological station from 1971 to 2020 and utilised in this study to assess model performance. Performance of each approach is assessed utilising root mean squared error (RMSE), Nash Sutcliffe efficiency (NSE), and Willmott index (WI). Results specify that the hybrid GRNN-FOA model is consistent and accurate in estimating the risk level of significant rainfall events. Our proposed robust model shows improved performance than conventional techniques, providing a new thought in the area of rainfall prediction. This artificial intelligence-based study would also help quickly and accurately predicting monthly rainfall.

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Author information

Authors and Affiliations

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

    Deba Prakash Satapathy, Harapriya Swain & Sandeep Samantaray

  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. Deba Prakash Satapathy
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  2. Harapriya Swain
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  3. Abinash Sahoo
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  4. Sandeep Samantaray
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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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Satapathy, D.P., Swain, H., Sahoo, A., Samantaray, S., Satapathy, S.C. (2023). Application of a Combined GRNN-FOA Model for Monthly Rainfall Forecasting in Northern Odisha, India. 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_34

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