IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v78y2005i3p195-208.html
   My bibliography  Save this article

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

Author

Listed:
  • Sarangi, A.
  • Bhattacharya, A.K.

Abstract

No abstract is available for this item.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378-3774(05)00071-5
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. Zhang, WenJun & Zhang, XiYan, 2008. "Neural network modeling of survival dynamics of holometabolous insects: A case study," Ecological Modelling, Elsevier, vol. 211(3), pages 433-443.
    5. 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.
    6. Zhang, WenJun & Bai, ChangJun & Liu, GuoDao, 2007. "Neural network modeling of ecosystems: A case study on cabbage growth system," Ecological Modelling, Elsevier, vol. 201(3), pages 317-325.
    7. 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.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:78:y:2005:i:3:p:195-208. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.