ارزیابی حساسیت رخداد زمین‌لغزش با استفاده از الگوریتم ماشین بردار پشتیبان

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Dastranj, A., & Karimi, E. (2022). Landslide susceptibility predicting using the maximum entropy machine learning algorithm (Bar catchment of Nishapur). Researches in Earth Sciences, 13(3), 76-96. doi:10.48308/esrj.2022.102965. [In Persian]

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Hallaji, M., Zanganeh Asadi, M.A., & Amirahmadi, A. (2020). An Assessment of the landslide susceptibility prediction models in the Bar Watershed-Neyshabur. Watershed Management Researches, 33(2), 20-30. doi:10.22092/wmej.2019.126950.1241. [In Persian]

Hong, H., Pradhan, B., Xu, C., & Bui, D.T. (2015). Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines. Catena, 133, 266-281. doi:10.1016/j.catena.2015.05.019

Lee, S., Hong, S.M., & Jung, H.S. (2017). A support vector machine for landslide susceptibility mapping in Gangwon Province, Korea. Sustainability, 9(1), 48.  doi:10.3390/su9010048

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Mohammadi, N., & Sasanpour, F. (2021). Risk analysis of landslide and debris flow occurrence on the Haraz and Lavasanat roads. Water and Soil Modeling and Management, 1(4),14-29. doi:10.22098/mmws.2021.9138. 1023 [In Persian]

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Pham, B.T., Prakash, I., Khosravi, K., Chapi, K., Trinh, P.T., Ngo, T.Q., Hosseini, S.V. and Bui, D.T. Pham, B.T., Prakash, I., Khosravi, K., Chapi, K., Trinh, P.T., Ngo, T. Q., . Hosseini, S.V., & Bui, D. T. (2019). A comparison of support vector machines and Bayesian algorithms for landslide susceptibility modelling. Geocarto International, 34(13), 1385-1407. doi:10.1080/10106049.2018.1489422

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Rostamizad, G. (2023). Assessing the potential and risk of landslides in Zanjan province (study area: Chesb watershed). A research project supported by the support of researchers and technologists of the country. 123 p. [In Persian]

Rostamizad, G., Khanbabaei, Z., & Tahamoures, M. (2022). Assessing the validity of the classification algorithms reviewed for the role of land use (Study: Taham Watershed). Environmental Erosion Research Journal, 12(4), 141-157.  http://magazine.hormozgan.ac.ir/article-1-710-fa.html. [In Persian]

Sepahvand, A.R., & Beiranvand, N. (2024). Mapping the susceptibility of landslide occurrence using machine learning algorithms (Study area: part of the Haraz watershed). Water and Soil Modeling and Management, 4(2), 261-278. doi:10.22098/mmws.2023. 12678.1263. [In Persian]

Shano, L., Raghuvanshi, T.K., & Meten, M. (2021). Landslide hazard zonation using logistic regression model: the Case of Shafe and Baso Catchments, Gamo Highland, Southern Ethiopia. Geotechnical and Geological Engineering, 1-19. doi:10.1007/s10706-021-01873-1

Suyarto, R., Diara, I.W., Susila, K.D., Saifulloh, M., Wiyanti, W., Kusmiyarti, T.B., & Sunarta, I.N. (2023). Landslide inventory mapping derived from multispectral imagery by support vector machine (SVM) algorithm. In IOP Conference Series: Earth and Environmental Science, 1190, (1), 012012. doi:10.1088/1755-1315/1190/1/012012

Tyagi, A., Tiwari, R.K., & James, N. (2021). GIS-based landslide hazard zonation and risk studies using MCDM. In Local Site Effects and Ground Failures: Select Proceedings of 7^th ICRAGEE 2020 (pp. 251-266). Springer Singapore.‏ doi:10.1007/978-981-15-9984-2_22

Wang, Z., & Brenning, A. (2021). Active-learning approaches for landslide mapping using support vector machines. Remote Sensing, 13(13), 2588. doi:10.3390/rs13132588

Wu, W., Zucca, C., Muhaimeed, A.S., Al-Shafie, W.M., Al-Quraishi, A.M.F., Nangia, V., Zhu MinQiang, Z.M., & Liu GuangPing, L.G.,Wu, W., Zucca, C., Muhaimeed, A.S., Al‐Shafie, W.M., Fadhil Al‐Quraishi, A.M., Nangia, V., Zhu, M., Liu, G. (2018). Soil salinity prediction and mapping by machine learning regression in Central Mesopotamia, Iraq. Land Degradation & Development, 29(11), 4005-4014. doi:10.1002/ldr.3148

Yarahmadi, J., Amini, A., & Rostamizad, G. (2023). Accuracy assessment of pistachio climate suitability map based on ROC curve. Environment and Water Engineering, 9(1), 127-140. doi:10.22034/jewe.2021.262531.1486. [In Persian]

Zali, M., & Shahedi, K. (2021). Assessment of landslide sensitivity using fuzzy logic approach and geographic information systems in the Nekarud watershed. Water and Soil Modeling and Management, 1(1), 67-80. doi:10.22098/mmws.2021.1183 [In Persian]

Zhou, X., Wu, W., Lin, Z., Zhang, G., Chen, R., Song, Y., Wang, Z., Lang, T., Qin, Y., Ou, P., Huangfu, W., Zhang, Y., Xie, L., Huang, X., Fu, X., Li, J., Jiang, J., Zhang, M., Liu, Y., Peng, Sh., Shao, C., Bai, Y., Zhang, X., Liu, X., & Liu, W. (2020). Landslide risk zoning in Ruijin, Jiangxi, China. Natural Hazards and Earth System Sciences Discussions, 1-21. doi:10.5194/nhess-2020-270

Zhu, A.X., Miao, Y., Liu, J., Bai, S., Zeng, C., Ma, T., & Hong, H. (2019). A similarity-based approach to sampling absence data for landslide susceptibility mapping using data-driven methods. Catena, 183, 104188. doi:10.1016/j.catena.2019.104188