آرین تبار، ح.، شرفی، س، و نگهبان، س.، 1399. ارزیابی روش جمع کیفی (QS) جهت تعیین گامای بهینه در تهیه نقشه پهنهبندی خطر زمینلغزش (مطالعه موردی: جنگل توسکستان تا گرگان)، پژوهشهای ژئومورفولوژی کمّی، دوره 9، شماره 3، صص 70-87.
رضوی ترمه، س و، و شیرانی، ک.، 1397. پهنهبندی خطر وقوع زمینلغزش با استفاده از روشهای نسبت فراوانی، آنتروپی و روش تصمیمگیری تاپسیس (مطالعه موردی: حوزه فهلیان، فارس)، سنجشازدور و سامانه اطلاعات جغرافیایی در منابع طبیعی، دوره 9، شماره 4، صص 119-138.
عرب عامری، ع.، شیرانی، ک، و رضایی، خ.، ۱۳۹۶. ارزیابی مقایسهای روشهای احتمالاتی وزن واقعه و نسبت فراوانی در پهنهبندی خطر زمینلغزش (مطالعه موردی: حوزه آبخیز ونک، اصفهان)، پژوهشنامه مدیریت حوزه آبخیز، دوره 8، شماره 15، صص 147-160.
عمادالدین، س.، طاهری، و.، محمدقاسمی، م، و نظری گزیک، ز.، 1400. پهنهبندی حساسیت زمینلغزش با استفاده از مدلهای نسبت فراوانی و شاخص آماری در حوضه آبخیز اوغان، پژوهشهای ژئومورفولوژی کمّی، دوره 9، شماره 4، صص 75-95.
غلامی، م.، سلیمانی، ک، و نکویی قاچکانلو، ا.، 1396. تهیهی نقشهی حساسیت به وقوع زمین لغزش با استفاده از مدلهای وزن شواهد (WofE)، نسبت فراوانی (FR) و دمپستر– شیفر (DSH) مطالعه ی موردی: محدوده ی ساری-کیاسر)، مرتع و آبخیزداری (منابع طبیعی ایران)، دوره 70، شماره 3، صص 735-750.
محمدنیا، م.، امیراحمدی، ا، و سلگی، ل.، 1393. تهیهی نقشهی حساسیت زمینلغزش با استفاده از مدل تلفیقی نسبت فراوانی و فرآیند تحلیل سلسله مراتبی، ژئوموروفولوژی کاربردی ایران، دوره 3، شماره 5، 45-58.
Abdo, H. G. (2021). Assessment of landslide susceptibility zonation using frequency ratio and statistical index: a case study of Al-Fawar basin, Tartous, Syria, International Journal of Environmental Science and Technology, 19(4), 2599-2618.
Aditian, A., Kubota, T., & Shinohara, Y. (2018). Comparison of GIS-based landslide susceptibility models using frequency ratio, logistic regression, and artificial neural network in a tertiary region of Ambon, Indonesia. Geomorphology, 318, 101-111.
Akinci, H., & Yavuz Ozalp, A. (2021). Landslide susceptibility mapping and hazard assessment in Artvin (Turkey) using frequency ratio and modified information value model. Acta Geophysica, 69(3), 725-745.
Berhane, G., Kebede, M., & Alfarrah, N. (2021). Landslide susceptibility mapping and rock slope stability assessment using frequency ratio and kinematic analysis in the mountains of Mgulat area, Northern Ethiopia. Bulletin of Engineering Geology and the Environment, 80(1), 285-301.
Berhane, G., Kebede, M., Alfarah, N., Hagos, E., Grum, B., Giday, A., & Abera, T. (2020). Landslide susceptibility zonation mapping using GIS-based frequency ratio model with multi-class spatial data-sets in the Adwa-Adigrat mountain chains, northern Ethiopia. Journal of African Earth Sciences, 164, 1-15.
Bousquet, O., von Luxburg, U., & Rätsch, G. (Eds.). (2011). Advanced Lectures on Machine Learning: ML Summer Schools 2003, Canberra, Australia, February 2-14, 2003, Tübingen, Germany, August 4-16, 2003, Revised Lectures (Vol. 3176). Springer.
Chen, W., Chai, H., Sun, X., Wang, Q., Ding, X., & Hong, H. (2016). A GIS-based comparative study of frequency ratio, statistical index and weights-of-evidence models in landslide susceptibility mapping. Arabian Journal of Geosciences, 9(3), 1-16.
Chen, W., Ding, X., Zhao, R., & Shi, S. (2016). Application of frequency ratio and weights of evidence models in landslide susceptibility mapping for the Shangzhou District of Shangluo City, China. Environmental Earth Sciences, 75(1), 1-10.
Chen, W., Li, W., Hou, E., Bai, H., Chai, H., Wang, D., ... & Wang, Q. (2015). Application of frequency ratio, statistical index, and index of entropy models and their comparison in landslide susceptibility mapping for the Baozhong Region of Baoji, China. Arabian Journal of Geosciences, 8(4), 1829-1841.
Chen, W., Pourghasemi, H. R., Panahi, M., Kornejady, A., Wang, J., Xie, X., & Cao, S. (2017). Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques. Geomorphology, 297, 69-85.
Chen, X., & Chen, W. (2021). GIS-based landslide susceptibility assessment using optimized hybrid machine learning methods. Catena, 196, 104833.
Dam, N. D., Amiri, M., Al-Ansari, N., Prakash, I., Le, H. V., Nguyen, H. B. T., & Pham, B. T. (2022). Evaluation of Shannon Entropy and Weights of Evidence Models in Landslide Susceptibility Mapping for the Pithoragarh District of Uttarakhand State, India. Advances in Civil Engineering, 2022, 1-16.
Ding, Q., Chen, W., & Hong, H. (2017). Application of frequency ratio, weights of evidence and evidential belief function models in landslide susceptibility mapping. Geocarto international, 32(6), 619-639.
Dou, J., Yunus, A. P., Bui, D. T., Merghadi, A., Sahana, M., Zhu, Z., ... & Pham, B. T. (2019). Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan. Science of the total environment, 662, 332-346.
Elvis, B. W. W., Arsène, M., Théophile, N. M., Bruno, K. M. E., & Olivier, O. A. (2022). Integration of shannon entropy (SE), frequency ratio (FR) and analytical hierarchy process (AHP) in GIS for suitable groundwater potential zones targeting in the Yoyo river basin, Méiganga area, Adamawa Cameroon. Journal of Hydrology: Regional Studies, 39, 100997, 1-24.
Es-smairi, A., Elmoutchou, B., Mir, R. A., Touhami, A. E. O., & Namous, M. (2022). Spatial prediction of landslide susceptibility using Frequency Ration (FR) and Shannon Entropy (SE) models: a case study from northern Rif, Morocco, 1-30.
Fayez, L., Pazhman, D., Pham, B. T., Dholakia, M. B., Solanki, H. A., Khalid, M., & Prakash, I. (2018). Application of frequency ratio model for the development of landslide susceptibility mapping at part of Uttarakhand State, India. Int. J. Appl. Eng. Res, 13(9), 6846-6854.
Guo, C., Montgomery, D. R., Zhang, Y., Wang, K., & Yang, Z. (2015). Quantitative assessment of landslide susceptibility along the Xianshuihe fault zone, Tibetan Plateau, China. Geomorphology, 248, 93-110.
Hodasová, K., & Bednarik, M. (2021). Effect of using various weighting methods in a process of landslide susceptibility assessment. Natural Hazards, 105(1), 481-499.
Huang, F., Yao, C., Liu, W., Li, Y., & Liu, X. (2018). Landslide susceptibility assessment in the Nantian area of China: a comparison of frequency ratio model and support vector machine. Geomatics, Natural Hazards and Risk, 9(1), 919-938.
Jennifer, J. J., Saravanan, S., & Abijith, D. (2021). Application of Frequency Ratio and Logistic Regression Model in the Assessment of Landslide Susceptibility Mapping for Nilgiris District, Tamilnadu, India. Indian Geotechnical Journal, 51(4), 773-787.
Khan, H., Shafique, M., Khan, M. A., Bacha, M. A., Shah, S. U., & Calligaris, C. (2019). Landslide susceptibility assessment using Frequency Ratio, a case study of northern Pakistan. The Egyptian Journal of Remote Sensing and Space Science, 22(1), 11-24.
Li, B., Wang, N., & Chen, J. (2021). GIS-based landslide susceptibility mapping using information, frequency ratio, and artificial neural network methods in Qinghai Province, Northwestern China. Advances in Civil Engineering, 2021, 1-14.
Liu, H., Li, X., Meng, T., & Liu, Y. (2020). Susceptibility mapping of damming landslide based on slope unit using frequency ratio model. Arabian Journal of Geosciences, 13(16), 1-19.
Melese, T., Belay, T., & Andemo, A. (2022). Application of analytical hierarchal process, frequency ratio, and Shannon entropy approaches for landslide susceptibility mapping using geospatial technology: The case of Dejen district, Ethiopia. Arabian Journal of Geosciences, 15(5), 1-21.
Morino, C., Coratza, P., & Soldati, M. (2022). Landslides, a Key Landform in the Global Geological Heritage.1-20.
Nanda, A. M., Ahmed, P., & Kanth, T. A. (2021). Landslide susceptibility assessment of national highway 1D from Sonamarg to Kargil, Jammu and Kashmir, India using frequency ratio method. GeoJournal, 86(6), 2945-2956.
Nicu, I. C. (2018). Application of analytic hierarchy process, frequency ratio, and statistical index to landslide susceptibility: an approach to endangered cultural heritage. Environmental earth sciences, 77(3), 1-16.
Ozdemir, A., & Altural, T. (2013). A comparative study of frequency ratio, weights of evidence and logistic regression methods for landslide susceptibility mapping: Sultan Mountains, SW Turkey. Journal of Asian Earth Sciences, 64, 180-197.
Panchal, S., & Shrivastava, A. K. (2021). A comparative study of frequency ratio, Shannon’s entropy and analytic hierarchy process (AHP) models for landslide susceptibility assessment. ISPRS International Journal of Geo-Information, 10(9), 603.
Rahman, G., Rahman, A. U., Bacha, A. S., Mahmood, S., Moazzam, M. F. U., & Lee, B. G. (2020). Assessment of landslide susceptibility using weight of evidence and frequency ratio model in Shahpur Valley, Eastern Hindu Kush. Natural Hazards and Earth System Sciences Discussions, 1-19.
Riaz, M. T., Basharat, M., Hameed, N., Shafique, M., & Luo, J. (2018). A data-driven approach to landslide-susceptibility mapping in mountainous terrain: case study from the Northwest Himalayas, Pakistan. Natural Hazards Review, 19(4), 05018007, 1-20.
Saranaathan, S. E., Mani, S., Ramesh, V., & Prasanna Venkatesh, S. (2021). Landslide susceptibility zonation mapping using bivariate statistical frequency ratio method and GIS: a case study in part of SH 37 Ghat Road, Nadugani, Panthalur Taluk, The Nilgiris. Journal of the Indian Society of Remote Sensing, 49(2), 275-291.
Shano, L., Raghuvanshi, T. K., & Meten, M. (2021). Landslide susceptibility mapping using frequency ratio model: the case of Gamo highland, South Ethiopia. Arabian Journal of Geosciences, 14(7), 1-18.
Shu, H., Guo, Z., Qi, S., Song, D., Pourghasemi, H. R., & Ma, J. (2021). Integrating Landslide Typology with Weighted Frequency Ratio Model for Landslide Susceptibility Mapping: A Case Study from Lanzhou City of Northwestern China. Remote Sensing, 13(18), 3623, 1-32.
Silalahi, F. E. S., Arifianti, Y., & Hidayat, F. (2019). Landslide susceptibility assessment using frequency ratio model in Bogor, West Java, Indonesia. Geoscience Letters, 6(1), 1-17.
Vakhshoori, V., & Zare, M. (2016). Landslide susceptibility mapping by comparing weight of evidence, fuzzy logic, and frequency ratio methods. Geomatics, Natural Hazards and Risk, 7(5), 1731-1752.
Wang, L. J., Guo, M., Sawada, K., Lin, J., & Zhang, J. (2016). A comparative study of landslide susceptibility maps using logistic regression, frequency ratio, decision tree, weights of evidence and artificial neural network. Geosciences Journal, 20(1), 117-136.
Wang, Q., Li, W., Yan, S., Wu, Y., & Pei, Y. (2016). GIS based frequency ratio and index of entropy models to landslide susceptibility mapping (Daguan, China). Environmental Earth Sciences, 75(9), 1-16.
Wu, Y., Li, W., Wang, Q., Liu, Q., Yang, D., Xing, M., ... & Yan, S. (2016). Landslide susceptibility assessment using frequency ratio, statistical index and certainty factor models for the Gangu County, China. Arabian Journal of Geosciences, 9(2), 1-16.
Wubalem, A. (2021). Landslide susceptibility mapping using statistical methods in Uatzau catchment area, northwestern Ethiopia. Geoenvironmental Disasters, 8(1), 1-21.
Yan, F., Zhang, Q., Ye, S., & Ren, B. (2019). A novel hybrid approach for landslide susceptibility mapping integrating analytical hierarchy process and normalized frequency ratio methods with the cloud model. Geomorphology, 327, 170-187.
Zhang, Y. X., Lan, H. X., Li, L. P., Wu, Y. M., Chen, J. H., & Tian, N. M. (2020). Optimizing the frequency ratio method for landslide susceptibility assessment: A case study of the Caiyuan Basin in the southeast mountainous area of China. Journal of Mountain Science, 17(2), 340-357.