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Information Journal Paper

Title

ANALYSIS AND INVESTIGATION OF LANDSLIDE HAZARD ZONING USING OF HIERARCHICAL ANALYSIS AND ARTIFICIAL NEURAL NETWORK MODELS IN THE SOUTHERN FOOTHILLS OF THE ALBORZ (TAJRISH OF TEHRAN)

Pages

  85-97

Keywords

AHPQ2
ANNQ2

Abstract

 In this research, by review of previous works and field works, the Nine factors identified effective factors in landslide hazard and used for analysis risk by GIS software. the occurred land slides in the study area were gathered and rectified by GPS. These Nine maps were crossed with the occurred landslide map and Landslides amounts and their areas were computed in each class. After determining the rate of each factor (element), land slide zonation was performed in GIS by artificial neural network and AHP Models. The efficiency of output results of models was assessed by DR and QS indices. The results of DR index showed The map was produced using a neural network than maps produced using the analytic hierarchy higher accuracy for the study area.

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    Cite

    APA: Copy

    RANJBAR, MOHSEN, & FADAK, ASAL. (2014). ANALYSIS AND INVESTIGATION OF LANDSLIDE HAZARD ZONING USING OF HIERARCHICAL ANALYSIS AND ARTIFICIAL NEURAL NETWORK MODELS IN THE SOUTHERN FOOTHILLS OF THE ALBORZ (TAJRISH OF TEHRAN). GEOGRAPHICAL JOURNAL OF TERRITORY, 11(43), 85-97. SID. https://sid.ir/paper/116203/en

    Vancouver: Copy

    RANJBAR MOHSEN, FADAK ASAL. ANALYSIS AND INVESTIGATION OF LANDSLIDE HAZARD ZONING USING OF HIERARCHICAL ANALYSIS AND ARTIFICIAL NEURAL NETWORK MODELS IN THE SOUTHERN FOOTHILLS OF THE ALBORZ (TAJRISH OF TEHRAN). GEOGRAPHICAL JOURNAL OF TERRITORY[Internet]. 2014;11(43):85-97. Available from: https://sid.ir/paper/116203/en

    IEEE: Copy

    MOHSEN RANJBAR, and ASAL FADAK, “ANALYSIS AND INVESTIGATION OF LANDSLIDE HAZARD ZONING USING OF HIERARCHICAL ANALYSIS AND ARTIFICIAL NEURAL NETWORK MODELS IN THE SOUTHERN FOOTHILLS OF THE ALBORZ (TAJRISH OF TEHRAN),” GEOGRAPHICAL JOURNAL OF TERRITORY, vol. 11, no. 43, pp. 85–97, 2014, [Online]. Available: https://sid.ir/paper/116203/en

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