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• W4367023068 abstract "One of the most crucial features in ensuring reliable and resilient water resource management and planning is accurate streamflow forecasting. It is critical for hydropower generation, flood management, and agricultural planning. Due to the sheer importance of streamflow forecasting, in this study the Grey Wolf optimization algorithm (GWO) is used to optimize the Adaptive Neuro-Fuzzy Inference System (ANFIS), and the model performance is compared to that of the standalone ANFIS model. Considering the importance of rainfall in streamflow forecasting, these parameters are used as input to the model for forecasting the streamflow in Mahanadi River, India. To assess the efficacy of our suggested model WI, NSE and MSE were used and it is found that ANFIS-GWO model outperforms than ANFIS model in streamflow forecasting." @default.
• W4367023068 created "2023-04-27" @default.
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• W4367023068 date "2023-01-01" @default.
• W4367023068 modified "2023-10-16" @default.
• W4367023068 title "Streamflow Forecasting Using Novel ANFIS-GWO Approach" @default.
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• W4367023068 doi "https://doi.org/10.1007/978-981-19-7513-4_13" @default.
• W4367023068 hasPublicationYear "2023" @default.
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