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Information Journal Paper

Title

THE ZONING OF SLOP INSTABILITIES ON THE MOUNTAIN ROADS BY ARTIFICIAL NEURAL NETWORK (MLP) (CASE STUDY: DARE DIZ STRAIT)

Pages

  19-35

Keywords

ARTIFICIAL NETWORK MULTI-LAYER PERCEPTRON (MLP)Q1

Abstract

 Dre Diz strait is one of the most risky straits of east Azarbayjian province from occurrence of slop instabilities. Given, the coincidence of this strait on the only connection pass between MARAND_JOLFA towns, the best way to care and keeping the security of the road, is identification of risky areas or zoning the risk of SLOP INSTABILITY in this strait. For this, the main data was collected then the needful layers were provided on the GIS software environment, later the zoning map of SLOP INSTABILITY for zoning SLOP INSTABILITY risk obtained in IDRISI software and on the ANN method (MLP) with 1-10-15 instruction provided, and the apt areas for occurrence of SLOP INSTABILITY have been introduced in five different risk class: highest, high, medium, low, very low. And according to the result slop and distance of fault have the greater role on the happening of slop instabilities on the strait and therefor on the Insecurity of the road.

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  • Cite

    APA: Copy

    ROOSTAEI, S., & KHODAEI, F.. (2016). THE ZONING OF SLOP INSTABILITIES ON THE MOUNTAIN ROADS BY ARTIFICIAL NEURAL NETWORK (MLP) (CASE STUDY: DARE DIZ STRAIT). JOURNAL OF PHYSICAL GEOGRAPHY, 9(3 (33)), 19-35. SID. https://sid.ir/paper/184983/en

    Vancouver: Copy

    ROOSTAEI S., KHODAEI F.. THE ZONING OF SLOP INSTABILITIES ON THE MOUNTAIN ROADS BY ARTIFICIAL NEURAL NETWORK (MLP) (CASE STUDY: DARE DIZ STRAIT). JOURNAL OF PHYSICAL GEOGRAPHY[Internet]. 2016;9(3 (33)):19-35. Available from: https://sid.ir/paper/184983/en

    IEEE: Copy

    S. ROOSTAEI, and F. KHODAEI, “THE ZONING OF SLOP INSTABILITIES ON THE MOUNTAIN ROADS BY ARTIFICIAL NEURAL NETWORK (MLP) (CASE STUDY: DARE DIZ STRAIT),” JOURNAL OF PHYSICAL GEOGRAPHY, vol. 9, no. 3 (33), pp. 19–35, 2016, [Online]. Available: https://sid.ir/paper/184983/en

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