104 citations as recorded by crossref.

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42. Utilization of Support Vector Models and Gene Expression Programming for Soil Strength Modeling A. Tenpe & A. Patel https://doi.org/10.1007/s13369-020-04441-6
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46. A hybrid machine learning and computing model for forecasting displacement of multifactor-induced landslides X. Zhu et al. https://doi.org/10.1007/s00521-017-2968-x
47. Input-parameter optimization using a SVR based ensemble model to predict landslide displacements in a reservoir area – A comparative study J. Zhang et al. https://doi.org/10.1016/j.asoc.2023.111107
48. Application of Support Vector Machine Algorithm Incorporating Slime Mould Algorithm Strategy in Ancient Glass Classification Y. Guo et al. https://doi.org/10.3390/app13063718
49. A Cuckoo Search-Support Vector Machine Model for Predicting Dynamic Measurement Errors of Sensors M. Jiang et al. https://doi.org/10.1109/ACCESS.2016.2605041
50. The effectiveness of a drainage tunnel in increasing the rainfall threshold of a deep-seated landslide Z. Wei et al. https://doi.org/10.1007/s10346-019-01241-4
51. Estuary salinity prediction using a coupled GA-SVM model: a case study of the Min River Estuary, China Y. Fang et al. https://doi.org/10.2166/ws.2016.097
52. A semantic information-driven stepwise landslide displacement prediction model F. Tang et al. https://doi.org/10.1007/s10661-022-10417-w
53. Suspended sediment yield estimation using genetic algorithm-based artificial intelligence models: case study of Mahanadi River, India A. Yadav et al. https://doi.org/10.1080/02626667.2018.1483581
54. Using color and 3D geometry features to segment fruit point cloud and improve fruit recognition accuracy G. Wu et al. https://doi.org/10.1016/j.compag.2020.105475
55. Automatic apple recognition based on the fusion of color and 3D feature for robotic fruit picking Y. Tao & J. Zhou https://doi.org/10.1016/j.compag.2017.09.019
56. A novel hybrid algorithm with static and dynamic models for air quality index forecasting X. Zhao et al. https://doi.org/10.1007/s11071-023-08552-1
57. Toward the reliable prediction of reservoir landslide displacement using earthworm optimization algorithm-optimized support vector regression (EOA-SVR) Z. Liu et al. https://doi.org/10.1007/s11069-023-06322-1
58. Prediction of landslide displacement based on GA-LSSVM with multiple factors Z. Cai et al. https://doi.org/10.1007/s10064-015-0804-z
59. SVM‐based hybrid approach for corridor‐level travel‐time estimation R. Sharmila et al. https://doi.org/10.1049/iet-its.2018.5069
60. Landslide Susceptibility Mapping Using the Slope Unit for Southeastern Helong City, Jilin Province, China: A Comparison of ANN and SVM C. Yu & J. Chen https://doi.org/10.3390/sym12061047
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62. Predicting the Deformation of a Slope Using a Random Coefficient Panel Data Model Z. Yuan et al. https://doi.org/10.3390/fractalfract8070429
63. Comparison of LR, 5-CV SVM, GA SVM, and PSO SVM for landslide susceptibility assessment in Tibetan Plateau area, China Y. Zhang et al. https://doi.org/10.1007/s11629-022-7685-y
64. Dynamic prediction of landslide life expectancy using ensemble system incorporating classical prediction models and machine learning L. Liu et al. https://doi.org/10.1016/j.gsf.2023.101758
65. Modeling, evaluation and forecasting of suspended sediment load in Kal-e Shur River, Sabzevar Basin, in northeast of Iran M. Asadi et al. https://doi.org/10.1007/s13201-025-02361-0
66. Modeling and prediction of the specific heat capacity of Al2 O3/water nanofluids using hybrid genetic algorithm/support vector regression model I. Alade et al. https://doi.org/10.1016/j.nanoso.2018.12.001
67. Prediction of Slope Stability using Naive Bayes Classifier X. Feng et al. https://doi.org/10.1007/s12205-018-1337-3
68. A hybrid intelligent optimization approach to improving quality for serial multistage and multi-response coal preparation production systems X. Yin et al. https://doi.org/10.1016/j.jmsy.2018.05.006
69. A review of models for water level forecasting based on machine learning W. Wee et al. https://doi.org/10.1007/s12145-021-00664-9
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71. Sea level prediction using climatic variables: a comparative study of SVM and hybrid wavelet SVM approaches S. Sithara et al. https://doi.org/10.1007/s11600-020-00484-3
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74. Combining Numerical Simulation and Deep Learning for Landslide Displacement Prediction: An Attempt to Expand the Deep Learning Dataset W. Xu et al. https://doi.org/10.3390/su14116908
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