Predict soil erosion with artificial neural network in Tanakami (Japan)

A. Abdollahzadeh, M. Mukhlisin, A. E. Shafie

    Research output: Contribution to journalArticle

    5 Citations (Scopus)

    Abstract

    In recent years using artificial neural networks has increased as powerful tool with capability to predict linear and nonlinear relationships in complex engineering problems. Using this toolbox has been significant in different civil engineering fields, especially hydrological problems for various important parameters with different variables and complex mathematical equation. Predict soil erosion has been studied as one of the important parameters of the catchment management in this study. To obtain data artificial rainfall was used in a catchment located in Jakujo Rachidani in Tanakami area. Artificial network has developed foe predict soil erosion and this results compared with obtained results from Multi Linear Regression (MLR) . The results show high ability of ANN to Prediction of soil erosion compared to MLR. The performance of each model is evaluated using the Mean Square Error (MSE), Root Mean Square Error (RMSE) Correlation Coefficient(R), Correlation of determination (R2), Mean Absolute Relative Error (MARE).

    Original languageEnglish
    Pages (from-to)51-60
    Number of pages10
    JournalWSEAS Transactions on Computers
    Volume10
    Issue number2
    Publication statusPublished - Feb 2011

    Fingerprint

    Erosion
    Neural networks
    Soils
    Linear regression
    Mean square error
    Catchments
    Civil engineering
    Rain

    Keywords

    • Artificial neural network
    • Catchment
    • Mean Square Error
    • Modeling
    • Multi linear regression
    • Soil Erosion

    ASJC Scopus subject areas

    • Computer Science(all)

    Cite this

    Abdollahzadeh, A., Mukhlisin, M., & Shafie, A. E. (2011). Predict soil erosion with artificial neural network in Tanakami (Japan). WSEAS Transactions on Computers, 10(2), 51-60.

    Predict soil erosion with artificial neural network in Tanakami (Japan). / Abdollahzadeh, A.; Mukhlisin, M.; Shafie, A. E.

    In: WSEAS Transactions on Computers, Vol. 10, No. 2, 02.2011, p. 51-60.

    Research output: Contribution to journalArticle

    Abdollahzadeh, A, Mukhlisin, M & Shafie, AE 2011, 'Predict soil erosion with artificial neural network in Tanakami (Japan)', WSEAS Transactions on Computers, vol. 10, no. 2, pp. 51-60.
    Abdollahzadeh, A. ; Mukhlisin, M. ; Shafie, A. E. / Predict soil erosion with artificial neural network in Tanakami (Japan). In: WSEAS Transactions on Computers. 2011 ; Vol. 10, No. 2. pp. 51-60.
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