مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

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Cites:

Information Journal Paper

Title

AN ASSESSMENT OF THE ARTIFICIAL NEURAL NETWORKS TECHNIQUE TO GEOMORPHOLOGIC MODELING SEDIMENT YIELD (CASE STUDY SAMANDEGAN RIVER SYSTEM)

Pages

  5-9

Abstract

 Estimating correct volume of sediment in a fluvial system is one of the most important issues in water engineering, river engineering, water resources, facilities, structures, water and environmental projects and programs for the development of them.

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  • Cite

    APA: Copy

    VALI, A.A., RAMESHT, M.H., SEIF, A., & GHAZAVI, R.. (2012). AN ASSESSMENT OF THE ARTIFICIAL NEURAL NETWORKS TECHNIQUE TO GEOMORPHOLOGIC MODELING SEDIMENT YIELD (CASE STUDY SAMANDEGAN RIVER SYSTEM). GEOGRAPHY AND ENVIRONMENTAL PLANNING (UNIVERSITY OF ISFAHAN), 22(4 (44)), 5-9. SID. https://sid.ir/paper/577407/en

    Vancouver: Copy

    VALI A.A., RAMESHT M.H., SEIF A., GHAZAVI R.. AN ASSESSMENT OF THE ARTIFICIAL NEURAL NETWORKS TECHNIQUE TO GEOMORPHOLOGIC MODELING SEDIMENT YIELD (CASE STUDY SAMANDEGAN RIVER SYSTEM). GEOGRAPHY AND ENVIRONMENTAL PLANNING (UNIVERSITY OF ISFAHAN)[Internet]. 2012;22(4 (44)):5-9. Available from: https://sid.ir/paper/577407/en

    IEEE: Copy

    A.A. VALI, M.H. RAMESHT, A. SEIF, and R. GHAZAVI, “AN ASSESSMENT OF THE ARTIFICIAL NEURAL NETWORKS TECHNIQUE TO GEOMORPHOLOGIC MODELING SEDIMENT YIELD (CASE STUDY SAMANDEGAN RIVER SYSTEM),” GEOGRAPHY AND ENVIRONMENTAL PLANNING (UNIVERSITY OF ISFAHAN), vol. 22, no. 4 (44), pp. 5–9, 2012, [Online]. Available: https://sid.ir/paper/577407/en

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