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Volumn 78, Issue 3, 2015, Pages 1749-1776

An integrated artificial neural network model for the landslide susceptibility assessment of Osado Island, Japan

Author keywords

AUC; BPNN; Certainty factor; Landslide susceptibility; Osado Island

Indexed keywords

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; DIGITAL ELEVATION MODEL; GEOLOGICAL SURVEY; GIS; INTEGRATED APPROACH; LANDSLIDE; SLOPE ANGLE;

EID: 84938990369     PISSN: 0921030X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11069-015-1799-2     Document Type: Article
Times cited : (208)

References (51)
  • 1
    • 0001813276 scopus 로고    scopus 로고
    • Landslide hazard assessment: summary review and new perspectives
    • Aleotti P, Chowdhury R (1999) Landslide hazard assessment: summary review and new perspectives. Bull Eng Geol Environ 58:21–44. doi:10.1007/s100640050066
    • (1999) Bull Eng Geol Environ , vol.58 , pp. 21-44
    • Aleotti, P.1    Chowdhury, R.2
  • 2
    • 1342330867 scopus 로고    scopus 로고
    • An artificial neural network approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas
    • Arora MK, Das Gupta AS, Gupta RP (2004) An artificial neural network approach for landslide hazard zonation in the Bhagirathi (Ganga) Valley, Himalayas. Int J Remote Sens 25:559–572. doi:10.1080/0143116031000156819
    • (2004) Int J Remote Sens , vol.25 , pp. 559-572
    • Arora, M.K.1    Das Gupta, A.S.2    Gupta, R.P.3
  • 3
    • 12344286175 scopus 로고    scopus 로고
    • The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan
    • Ayalew L, Yamagishi H (2005) The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology 65:15–31. doi:10.1016/j.geomorph.2004.06.010
    • (2005) Geomorphology , vol.65 , pp. 15-31
    • Ayalew, L.1    Yamagishi, H.2
  • 4
    • 28244443379 scopus 로고    scopus 로고
    • Landslides in Sado Island of Japan: part I. Case studies, monitoring techniques and environmental considerations
    • Ayalew L, Yamagishi H, Marui H, Kanno T (2005) Landslides in Sado Island of Japan: part I. Case studies, monitoring techniques and environmental considerations. Eng Geol 81:419–431
    • (2005) Eng Geol , vol.81 , pp. 419-431
    • Ayalew, L.1    Yamagishi, H.2    Marui, H.3    Kanno, T.4
  • 5
    • 0018441920 scopus 로고
    • A physically based, variable contributing area model of basin hydrology
    • Beven KJ, Kirkby MJ (1979) A physically based, variable contributing area model of basin hydrology. Hydrol Sci J 24:43–69
    • (1979) Hydrol Sci J , vol.24 , pp. 43-69
    • Beven, K.J.1    Kirkby, M.J.2
  • 6
    • 0031688283 scopus 로고    scopus 로고
    • Slope instability zonation: a comparison between certainty factor and fuzzy Dempster–Shafer approaches
    • Binaghi E, Luzi L, Madella P et al (1998) Slope instability zonation: a comparison between certainty factor and fuzzy Dempster–Shafer approaches. Nat Hazards 17:77–97. doi:10.1023/A:1008001724538
    • (1998) Nat Hazards , vol.17 , pp. 77-97
    • Binaghi, E.1    Luzi, L.2    Madella, P.3
  • 7
    • 0001078960 scopus 로고
    • Innovative approaches to landslide hazard mapping
    • Brabb EE (1984) Innovative approaches to landslide hazard mapping. Proc 4th Int Symp Landslides 1:307–324
    • (1984) Proc 4th Int Symp Landslides , vol.1 , pp. 307-324
    • Brabb, E.E.1
  • 8
    • 33744827118 scopus 로고    scopus 로고
    • Application of back-propagation networks in debris flow prediction
    • Chang T-C, Chao R-J (2006) Application of back-propagation networks in debris flow prediction. Eng Geol 85:270–280. doi:10.1016/j.enggeo.2006.02.007
    • (2006) Eng Geol , vol.85 , pp. 270-280
    • Chang, T.-C.1    Chao, R.-J.2
  • 9
    • 80053132937 scopus 로고    scopus 로고
    • Landslide susceptibility zonation through ratings derived from artificial neural network
    • Chauhan S, Sharma M, Arora MK, Gupta NK (2010) Landslide susceptibility zonation through ratings derived from artificial neural network. Int J Appl Earth Obs Geoinf 12:340–350. doi:10.1016/j.jag.2010.04.006
    • (2010) Int J Appl Earth Obs Geoinf , vol.12 , pp. 340-350
    • Chauhan, S.1    Sharma, M.2    Arora, M.K.3    Gupta, N.K.4
  • 10
    • 0027878572 scopus 로고
    • The representation of geoscience information for data integration
    • Chung C-J, Fabbri AG (1993) The representation of geoscience information for data integration. Nonrenewable Resour 2:122–139. doi:10.1007/BF02272809
    • (1993) Nonrenewable Resour , vol.2 , pp. 122-139
    • Chung, C.-J.1    Fabbri, A.G.2
  • 11
    • 84887624992 scopus 로고    scopus 로고
    • Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy)
    • Conforti M, Pascale S, Robustelli G, Sdao F (2014) Evaluation of prediction capability of the artificial neural networks for mapping landslide susceptibility in the Turbolo River catchment (northern Calabria, Italy). Catena 113:236–250. doi:10.1016/j.catena.2013.08.006
    • (2014) Catena , vol.113 , pp. 236-250
    • Conforti, M.1    Pascale, S.2    Robustelli, G.3    Sdao, F.4
  • 12
    • 70449560600 scopus 로고    scopus 로고
    • Landslides detection: a case study in Conghua city of Pearl River delta
    • Dou J, Qian J, Zhang H et al (2009) Landslides detection: a case study in Conghua city of Pearl River delta. Second Int Conf Earth Obs Glob Chang. doi:10.1117/12.836328
    • (2009) Second Int Conf Earth Obs Glob Chang
    • Dou, J.1    Qian, J.2    Zhang, H.3
  • 13
    • 84937915352 scopus 로고    scopus 로고
    • Susceptibility mapping using a certainty factor model and its validation in the Chuetsu area, Central Japan
    • Dou J, Oguchi T, Hayakawa YS et al (2014) Susceptibility mapping using a certainty factor model and its validation in the Chuetsu area, Central Japan. Landslide Sci Safer Geoenviron 2:483–489. doi:10.1007/978-3-319-05050-8_65
    • (2014) Landslide Sci Safer Geoenviron , vol.2 , pp. 483-489
    • Dou, J.1    Oguchi, T.2    Hayakawa, Y.S.3
  • 14
    • 84937898139 scopus 로고    scopus 로고
    • Automatic case-based reasoning approach for landslide detection: integration of object-oriented image analysis and a genetic algorithm
    • Dou J, Chang K, Chen S et al (2015a) Automatic case-based reasoning approach for landslide detection: integration of object-oriented image analysis and a genetic algorithm. Remote Sens. doi:10.3390/rs70404318
    • (2015) Remote Sens
    • Dou, J.1    Chang, K.2    Chen, S.3
  • 15
    • 84938983378 scopus 로고    scopus 로고
    • Automatic detection of sinkhole collapses at finer resolutions using a multi-component remote sensing approach
    • Dou J, Li X, Yunus AP et al (2015b) Automatic detection of sinkhole collapses at finer resolutions using a multi-component remote sensing approach. Nat Hazards 26:1–24. doi:10.1007/s11069-015-1756-0
    • (2015) Nat Hazards , vol.26
    • Dou, J.1    Li, X.2    Yunus, A.P.3
  • 16
    • 84983479538 scopus 로고    scopus 로고
    • Differentiation of shallow and deep-seated landslides using support vector machines: a case study of the Chuetsu area, Japan
    • Dou J, Paudel U, Oguchi T et al (2015c) Differentiation of shallow and deep-seated landslides using support vector machines: a case study of the Chuetsu area, Japan. Terr Atmos Ocean Sci 26:227–239. doi:10.3319/TAO.2014.12.02.07(EOSI)
    • (2015) Terr Atmos Ocean Sci , vol.26 , pp. 227-239
    • Dou, J.1    Paudel, U.2    Oguchi, T.3
  • 17
    • 68549085424 scopus 로고    scopus 로고
    • Logistic regression versus artificial neural networks: landslide susceptibility evaluation in a sample area of the Serchio River valley, Italy
    • Falaschi F, Giacomelli F, Federici PR et al (2009) Logistic regression versus artificial neural networks: landslide susceptibility evaluation in a sample area of the Serchio River valley, Italy. Nat Hazards 50:551–569
    • (2009) Nat Hazards , vol.50 , pp. 551-569
    • Falaschi, F.1    Giacomelli, F.2    Federici, P.R.3
  • 18
    • 80355132750 scopus 로고    scopus 로고
    • Neural network-based model for landslide susceptibility and soil longitudinal profile analyses: two case studies
    • Farrokhzad F, Barari A, Choobbasti AJ, Ibsen LB (2011) Neural network-based model for landslide susceptibility and soil longitudinal profile analyses: two case studies. J African Earth Sci 61:349–357. doi:10.1016/j.jafrearsci.2011.09.004
    • (2011) J African Earth Sci , vol.61 , pp. 349-357
    • Farrokhzad, F.1    Barari, A.2    Choobbasti, A.J.3    Ibsen, L.B.4
  • 19
    • 84891638337 scopus 로고    scopus 로고
    • A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis
    • Feizizadeh B, Jankowski P, Blaschke T (2014) A GIS based spatially-explicit sensitivity and uncertainty analysis approach for multi-criteria decision analysis. Comput Geosci 64:81–95. doi:10.1016/j.cageo.2013.11.009
    • (2014) Comput Geosci , vol.64 , pp. 81-95
    • Feizizadeh, B.1    Jankowski, P.2    Blaschke, T.3
  • 21
    • 0043231196 scopus 로고    scopus 로고
    • susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques
    • Gökceoglu C, Aksoy H (1996) susceptibility mapping of the slopes in the residual soils of the Mengen region (Turkey) by deterministic stability analyses and image processing techniques. Eng Geol 44:147–161
    • (1996) Eng Geol , vol.44 , pp. 147-161
    • Gökceoglu, C.1    Aksoy, H.2
  • 22
    • 0343069785 scopus 로고    scopus 로고
    • Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy
    • Guzzetti F, Carrara A, Cardinali M, Reichenbach P (1999) Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy. Geomorphology 31:181–216. doi:10.1016/S0169-555x(99)00078-1
    • (1999) Geomorphology , vol.31 , pp. 181-216
    • Guzzetti, F.1    Carrara, A.2    Cardinali, M.3    Reichenbach, P.4
  • 23
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • Hornik K, Stinchcombe M, White H (1989) Multilayer feedforward networks are universal approximators. Neural Netw 2:359–366
    • (1989) Neural Netw , vol.2 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 24
    • 33744829751 scopus 로고    scopus 로고
    • A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas
    • Kanungo DP, Arora MK, Sarkar S, Gupta RP (2006) A comparative study of conventional, ANN black box, fuzzy and combined neural and fuzzy weighting procedures for landslide susceptibility zonation in Darjeeling Himalayas. Eng Geol 85:347–366. doi:10.1016/j.enggeo.2006.03.004
    • (2006) Eng Geol , vol.85 , pp. 347-366
    • Kanungo, D.P.1    Arora, M.K.2    Sarkar, S.3    Gupta, R.P.4
  • 25
    • 80255137525 scopus 로고    scopus 로고
    • Combining neural network with fuzzy, certainty factor and likelihood ratio concepts for spatial prediction of landslides
    • Kanungo DP, Sarkar S, Sharma S (2011) Combining neural network with fuzzy, certainty factor and likelihood ratio concepts for spatial prediction of landslides. Nat Hazards 59:1491–1512. doi:10.1007/s11069-011-9847-z
    • (2011) Nat Hazards , vol.59 , pp. 1491-1512
    • Kanungo, D.P.1    Sarkar, S.2    Sharma, S.3
  • 26
    • 84883461868 scopus 로고    scopus 로고
    • Landslide temporal analysis and susceptibility assessment as bases for landslide mitigation, Machu Picchu, Peru
    • Klimes J (2013) Landslide temporal analysis and susceptibility assessment as bases for landslide mitigation, Machu Picchu, Peru. Environ Earth Sci 70:913–925. doi:10.1007/s12665-012-2181-2
    • (2013) Environ Earth Sci , vol.70 , pp. 913-925
    • Klimes, J.1
  • 27
    • 84866312529 scopus 로고    scopus 로고
    • Rainfall and earthquake-induced landslide susceptibility assessment using GIS and artificial neural network
    • Li Y, Chen G, Tang C et al (2012) Rainfall and earthquake-induced landslide susceptibility assessment using GIS and artificial neural network. Nat Hazards Earth Syst Sci 12:2719–2729. doi:10.5194/nhess-12-2719-2012
    • (2012) Nat Hazards Earth Syst Sci , vol.12 , pp. 2719-2729
    • Li, Y.1    Chen, G.2    Tang, C.3
  • 28
    • 34250613472 scopus 로고    scopus 로고
    • Segmentation and object-based classification for the extraction of the building class from LIDAR DEMs
    • Miliaresis G, Kokkas N (2007) Segmentation and object-based classification for the extraction of the building class from LIDAR DEMs. Comput Geosci 33:1076–1087. doi:10.1016/j.cageo.2006.11.012
    • (2007) Comput Geosci , vol.33 , pp. 1076-1087
    • Miliaresis, G.1    Kokkas, N.2
  • 29
    • 84879454846 scopus 로고    scopus 로고
    • A modified analytical hierarchy process (M-AHP) approach for decision support systems in natural hazard assessments
    • Nefeslioglu HA, Sezer EA, Gokceoglu C, Ayas Z (2013) A modified analytical hierarchy process (M-AHP) approach for decision support systems in natural hazard assessments. Comput Geosci 59:1–8. doi:10.1016/j.cageo.2013.05.010
    • (2013) Comput Geosci , vol.59
    • Nefeslioglu, H.A.1    Sezer, E.A.2    Gokceoglu, C.3    Ayas, Z.4
  • 30
    • 0030793935 scopus 로고    scopus 로고
    • Drainage density and relative relief in humid steep mountains with frequent slope failure
    • Oguchi T (1997) Drainage density and relative relief in humid steep mountains with frequent slope failure. Earth Surf Process Landforms 22:107–120
    • (1997) Earth Surf Process Landforms , vol.22 , pp. 107-120
    • Oguchi, T.1
  • 31
    • 84874117042 scopus 로고    scopus 로고
    • Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea
    • Park S, Choi C, Kim B, Kim J (2012) Landslide susceptibility mapping using frequency ratio, analytic hierarchy process, logistic regression, and artificial neural network methods at the Inje area, Korea. Environ Earth Sci 68:1443–1464. doi:10.1007/s12665-012-1842-5
    • (2012) Environ Earth Sci , vol.68 , pp. 1443-1464
    • Park, S.1    Choi, C.2    Kim, B.3    Kim, J.4
  • 32
    • 79952622937 scopus 로고    scopus 로고
    • An analysis of landslide susceptibility zonation using a subjective geomorphic mapping and existing landslides
    • Pavel M, Nelson JD, Jonathan Fannin R (2011) An analysis of landslide susceptibility zonation using a subjective geomorphic mapping and existing landslides. Comput Geosci 37:554–566. doi:10.1016/j.cageo.2010.10.006
    • (2011) Comput Geosci , vol.37 , pp. 554-566
    • Pavel, M.1    Nelson, J.D.2    Jonathan Fannin, R.3
  • 33
    • 84862318369 scopus 로고    scopus 로고
    • Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: safarood Basin
    • Pourghasemi HR, Mohammady M, Pradhan B (2012) Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: safarood Basin. Iran. Catena 97:71–84. doi:10.1016/j.catena.2012.05.005
    • (2012) Iran. Catena , vol.97 , pp. 71-84
    • Pourghasemi, H.R.1    Mohammady, M.2    Pradhan, B.3
  • 34
    • 84870850608 scopus 로고    scopus 로고
    • A comparative assessment of prediction capabilities of Dempster–Shafer and weights-of-evidence models in landslide susceptibility mapping using GIS
    • Pourghasemi H, Pradhan B, Gokceoglu C, Moezzi KD (2013) A comparative assessment of prediction capabilities of Dempster–Shafer and weights-of-evidence models in landslide susceptibility mapping using GIS. Geomatics Nat Hazards Risk 4:93–118. doi:10.1080/19475705.2012.662915
    • (2013) Geomatics Nat Hazards Risk , vol.4 , pp. 93-118
    • Pourghasemi, H.1    Pradhan, B.2    Gokceoglu, C.3    Moezzi, K.D.4
  • 35
    • 77952010906 scopus 로고    scopus 로고
    • A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses
    • Pradhan B, Lee S, Buchroithner MF (2010) A GIS-based back-propagation neural network model and its cross-application and validation for landslide susceptibility analyses. Comput Environ Urban Syst 34:216–235. doi:10.1016/j.compenvurbsys.2009.12.004
    • (2010) Comput Environ Urban Syst , vol.34 , pp. 216-235
    • Pradhan, B.1    Lee, S.2    Buchroithner, M.F.3
  • 36
    • 84862200782 scopus 로고    scopus 로고
    • Retrieval of spinach crop parameters by microwave remote sensing with back propagation artificial neural networks: a comparison of different transfer functions
    • Prasad R, Pandey A, Singh KP et al (2012) Retrieval of spinach crop parameters by microwave remote sensing with back propagation artificial neural networks: a comparison of different transfer functions. Adv Sp Res 50:363–370. doi:10.1016/j.asr.2012.04.010
    • (2012) Adv Sp Res , vol.50 , pp. 363-370
    • Prasad, R.1    Pandey, A.2    Singh, K.P.3
  • 37
    • 0022471098 scopus 로고
    • Learning representations by back-propagating errors
    • Rumelhart D, Hinton G, Williams R (1986) Learning representations by back-propagating errors. Nature 323:533–536
    • (1986) Nature , vol.323 , pp. 533-536
    • Rumelhart, D.1    Hinton, G.2    Williams, R.3
  • 38
    • 84860356620 scopus 로고    scopus 로고
    • Comparison of artificial neural network and logistic regression models for predicting in-hospital mortality after primary liver cancer surgery
    • Shi H-Y, Lee K-T, Lee H-H et al (2012) Comparison of artificial neural network and logistic regression models for predicting in-hospital mortality after primary liver cancer surgery. PLoS ONE 7:e35781. doi:10.1371/journal.pone.0035781
    • (2012) PLoS ONE , vol.7 , pp. 35781
    • Shi, H.-Y.1    Lee, K.-T.2    Lee, H.-H.3
  • 40
    • 17044428072 scopus 로고    scopus 로고
    • Comparative analysis of logistic regression and artificial neural network for computer-aided diagnosis of breast masses
    • Song JH, Venkatesh SS, Conant EA et al (2005) Comparative analysis of logistic regression and artificial neural network for computer-aided diagnosis of breast masses. Acad Radiol 12:487–495. doi:10.1016/j.acra.2004.12.016
    • (2005) Acad Radiol , vol.12 , pp. 487-495
    • Song, J.H.1    Venkatesh, S.S.2    Conant, E.A.3
  • 41
    • 84875774524 scopus 로고    scopus 로고
    • An adaptive fuzzy-genetic algorithm approach for building detection using high-resolution satellite images
    • Sumer E, Turker M (2013) An adaptive fuzzy-genetic algorithm approach for building detection using high-resolution satellite images. Comput Environ Urban Syst 39:48–62. doi:10.1016/j.compenvurbsys.2013.01.004
    • (2013) Comput Environ Urban Syst , vol.39 , pp. 48-62
    • Sumer, E.1    Turker, M.2
  • 42
    • 0023890867 scopus 로고
    • Measuring the accuracy of diagnostic systems
    • Swets JA (1988) Measuring the accuracy of diagnostic systems. Science 240:1285–1293
    • (1988) Science , vol.240 , pp. 1285-1293
    • Swets, J.A.1
  • 43
    • 84865535244 scopus 로고    scopus 로고
    • Landslide susceptibility assessment in the Hoa Binh province of Vietnam: a comparison of the Levenberg–Marquardt and Bayesian regularized neural networks
    • Tien Bui D, Pradhan B, Lofman O et al (2012) Landslide susceptibility assessment in the Hoa Binh province of Vietnam: a comparison of the Levenberg–Marquardt and Bayesian regularized neural networks. Geomorphology 171–172:12–29. doi:10.1016/j.geomorph.2012.04.023
    • (2012) Geomorphology , vol.171-172 , pp. 12-29
    • Tien Bui, D.1    Pradhan, B.2    Lofman, O.3
  • 45
    • 77955925179 scopus 로고    scopus 로고
    • A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping
    • Vahidnia MH, Alesheikh AA, Alimohammadi A, Hosseinali F (2010) A GIS-based neuro-fuzzy procedure for integrating knowledge and data in landslide susceptibility mapping. Comput Geosci 36:1101–1114. doi:10.1016/j.cageo.2010.04.004
    • (2010) Comput Geosci , vol.36 , pp. 1101-1114
    • Vahidnia, M.H.1    Alesheikh, A.A.2    Alimohammadi, A.3    Hosseinali, F.4
  • 46
    • 53249129573 scopus 로고    scopus 로고
    • Prediction of the occurrence of slope instability phenomenal through GIS-based hazard zonation
    • Van Westen CJ, Rengers N, Terlien MTJ, Soeters R (1997) Prediction of the occurrence of slope instability phenomenal through GIS-based hazard zonation. Geol Rundschau 86:404–414. doi:10.1007/s005310050149
    • (1997) Geol Rundschau , vol.86 , pp. 404-414
    • Van Westen, C.J.1    Rengers, N.2    Terlien, M.T.J.3    Soeters, R.4
  • 47
    • 84938953288 scopus 로고    scopus 로고
    • GIS mapping of landscape and disasters of Sado Island, Japan
    • Yamagishi H (2008) GIS mapping of landscape and disasters of Sado Island, Japan. Int Arch Photogramm Remote Sens Spat Inf Sci XXXVII:1429–1432 (Part B7, Beijing 2008)
    • (2008) Int Arch Photogramm Remote Sens Spat Inf Sci , vol.1429-1432
    • Yamagishi, H.1
  • 48
    • 21044454864 scopus 로고    scopus 로고
    • Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey)
    • Yesilnacar E, Topal T (2005) Landslide susceptibility mapping: a comparison of logistic regression and neural networks methods in a medium scale study, Hendek region (Turkey). Eng Geol 79:251–266. doi:10.1016/j.enggeo.2005.02.002
    • (2005) Eng Geol , vol.79 , pp. 251-266
    • Yesilnacar, E.1    Topal, T.2
  • 49
    • 64949164773 scopus 로고    scopus 로고
    • Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat—Turkey)
    • Yilmaz I (2009) Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: a case study from Kat landslides (Tokat—Turkey). Comput Geosci 35:1125–1138. doi:10.1016/j.cageo.2008.08.007
    • (2009) Comput Geosci , vol.35 , pp. 1125-1138
    • Yilmaz, I.1
  • 50
    • 84940451832 scopus 로고    scopus 로고
    • Landslide susceptibility assessment at Wadi Jawrah Basin
    • Saudi Arabia using two bivariate models in GIS, Geosci J
    • Youssef AM, Pradhan B, Pourghasemi HR, Abdullahi S (2015) Landslide susceptibility assessment at Wadi Jawrah Basin, Jizan region, Saudi Arabia using two bivariate models in GIS. Geosci J doi:10.1007/s12303-014-0065-z
    • (2015) Jizan region
    • Youssef, A.M.1    Pradhan, B.2    Pourghasemi, H.R.3    Abdullahi, S.4
  • 51
    • 84881426548 scopus 로고    scopus 로고
    • Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms
    • Zare M, Pourghasemi HR, Vafakhah M, Pradhan B (2013) Landslide susceptibility mapping at Vaz Watershed (Iran) using an artificial neural network model: a comparison between multilayer perceptron (MLP) and radial basic function (RBF) algorithms. Arab J Geosci 6:2873–2888. doi:10.1007/s12517-012-0610-x
    • (2013) Arab J Geosci , vol.6 , pp. 2873-2888
    • Zare, M.1    Pourghasemi, H.R.2    Vafakhah, M.3    Pradhan, B.4


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