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Comparison of Artificial Neural Network and regression models for sediment loss prediction from Banha watershed in India

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  • Sarangi, A.
  • Bhattacharya, A.K.

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  • Sarangi, A. & Bhattacharya, A.K., 2005. "Comparison of Artificial Neural Network and regression models for sediment loss prediction from Banha watershed in India," Agricultural Water Management, Elsevier, vol. 78(3), pages 195-208, December.
    • Handle: RePEc:eee:agiwat:v:78:y:2005:i:3:p:195-208
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    References listed on IDEAS

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    1. Sharma, V. & Negi, S. C. & Rudra, R. P. & Yang, S., 2003. "Neural networks for predicting nitrate-nitrogen in drainage water," Agricultural Water Management, Elsevier, vol. 63(3), pages 169-183, December.
    2. Kaur, Ravinder & Srinivasan, Raghavan & Mishra, Kamal & Dutta, D. & Prasad, Durga & Bansal, Gagan, 2003. "Assessment of a SWAT model for soil and water management in India," Land Use and Water Resources Research, University of Newcastle upon Tyne, Centre for Land Use and Water Resources Research, vol. 3, pages 1-7.
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    Cited by:

    1. Paresh Shirsath & Anil Singh, 2010. "A Comparative Study of Daily Pan Evaporation Estimation Using ANN, Regression and Climate Based Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(8), pages 1571-1581, June.
    2. Zaher Mundher Yaseen & Ozgur Kisi & Vahdettin Demir, 2016. "Enhancing Long-Term Streamflow Forecasting and Predicting using Periodicity Data Component: Application of Artificial Intelligence," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(12), pages 4125-4151, September.
    3. Zou, Ping & Yang, Jingsong & Fu, Jianrong & Liu, Guangming & Li, Dongshun, 2010. "Artificial neural network and time series models for predicting soil salt and water content," Agricultural Water Management, Elsevier, vol. 97(12), pages 2009-2019, November.
    4. Anctil, François & Filion, Mélanie & Tournebize, Julien, 2009. "A neural network experiment on the simulation of daily nitrate-nitrogen and suspended sediment fluxes from a small agricultural catchment," Ecological Modelling, Elsevier, vol. 220(6), pages 879-887.
    5. Sarangi, A. & Singh, Man & Bhattacharya, A.K. & Singh, A.K., 2006. "Subsurface drainage performance study using SALTMOD and ANN models," Agricultural Water Management, Elsevier, vol. 84(3), pages 240-248, August.
    6. J. Patil & A. Sarangi & O. Singh & A. Singh & T. Ahmad, 2008. "Development of a GIS Interface for Estimation of Runoff from Watersheds," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(9), pages 1221-1239, September.
    7. Liu, Xiaozhi & Kang, Shaozhong & Li, Fusheng, 2009. "Simulation of artificial neural network model for trunk sap flow of Pyrus pyrifolia and its comparison with multiple-linear regression," Agricultural Water Management, Elsevier, vol. 96(6), pages 939-945, June.
    8. Agnieszka Petryk & Edyta Kruk & Marek Ryczek & Lenka Lackóová, 2023. "Comparison of Pedotransfer Functions for Determination of Saturated Hydraulic Conductivity for Highly Eroded Loess Soil," Land, MDPI, vol. 12(3), pages 1-13, March.
    9. Pavitra Kumar & Sai Hin Lai & Jee Khai Wong & Nuruol Syuhadaa Mohd & Md Rowshon Kamal & Haitham Abdulmohsin Afan & Ali Najah Ahmed & Mohsen Sherif & Ahmed Sefelnasr & Ahmed El-Shafie, 2020. "Review of Nitrogen Compounds Prediction in Water Bodies Using Artificial Neural Networks and Other Models," Sustainability, MDPI, vol. 12(11), pages 1-26, May.

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