102 citations as recorded by crossref.

1. Displacement Prediction of the Muyubao Landslide Based on a GPS Time-Series Analysis and Temporal Convolutional Network Model D. Huang et al.
2. Application of wavelet analysis and a particle swarm-optimized support vector machine to predict the displacement of the Shuping landslide in the Three Gorges, China F. Ren et al.
3. Landslide susceptibility mapping and management in Western Serbia: an analysis of ANFIS- and SVM-based hybrid models I. Elkhrachy et al.
4. A comparative approach of support vector machine kernel functions for GIS-based landslide susceptibility mapping K. Kamran et al.
5. Displacement prediction of landslides at slope-scale: Review of physics-based and data-driven approaches W. Gong et al.
6. LEAST SQUARES SUPPORT VECTOR MACHINE MODEL FOR COORDINATE TRANSFORMATION Y. Ziggah et al.
7. Soft computing in assessment of earthquake-triggered landslide susceptibility C. Xu et al.
8. Landslide Displacement Prediction Based on Transfer Learning and Bi-GRU H. Zheng et al.
9. An interpretable model for landslide susceptibility assessment based on Optuna hyperparameter optimization and Random Forest X. Xiao et al.
10. Development of hybrid machine learning-based carbonation models with weighting function Z. Chen et al.
11. A novel landslide susceptibility optimization framework to assess landslide occurrence probability at the regional scale for environmental management X. Sun et al.
12. Landslide Deformation Analysis by Coupling Deformation Time Series from SAR Data with Hydrological Factors through Data Assimilation Y. Jiang et al.
13. Estimating the rainfall threshold of a deep-seated landslide by integrating models for predicting the groundwater level and stability analysis of the slope Z. Wei et al.
14. A WD-GA-LSSVM model for rainfall-triggered landslide displacement prediction X. Zhu et al.
15. Developing new tree expression programing and artificial bee colony technique for prediction and optimization of landslide movement Z. Luo et al.
16. Predicting of the refractive index of haemoglobin using the Hybrid GA-SVR approach T. Oyehan et al.
17. Ensemble learning for landslide displacement prediction: A perspective of Bayesian optimization and comparison of different time series analysis methods L. Liu et al.
18. A new method for displacement prediction of “step-like” landslides based on VMD-FOA-SVR model X. Lu et al.
19. A spatially explicit multi-hazard framework for assessing flood, landslide, wildfire, and drought susceptibilities B. Choubin et al.
20. Effective and Accelerated Forewarning of Landslides Using Wireless Sensor Networks and Machine Learning T. Hemalatha et al.
21. Use of ROC curves for early warning of landslide displacement rates in response to precipitation (Piagneto landslide, Northern Apennines, Italy) A. Corsini & M. Mulas
22. Overall grouting compactness detection of bridge prestressed bellows based on RF feature selection and the GA-SVM model H. Liu et al.
23. A Hybrid Random Forest and Least Squares Support Vector Machine Model Based on Particle Swarm Optimization Algorithm for Slope Stability Prediction: A Case Study in Sichuan–Tibet Highway, China T. Shu et al.
24. A Novel Hybrid LMD–ETS–TCN Approach for Predicting Landslide Displacement Based on GPS Time Series Analysis W. Luo et al.
25. Simultaneous state–parameter estimation of rainfall-induced landslide displacement using data assimilation J. Wang et al.
26. Understanding the Mechanisms of Earth Fissuring for Hazard Mitigation in Najran, Saudi Arabia M. Alsaiari et al.
27. A Hybrid Landslide Displacement Prediction Method Based on CEEMD and DTW-ACO-SVR—Cases Studied in the Three Gorges Reservoir Area J. Zhang et al.
28. A comparative study of mutual information-based input variable selection strategies for the displacement prediction of seepage-driven landslides using optimized support vector regression J. Ma et al.
29. Short-Term Prediction of Vertical Deformation in Tidal Flat Terrains Based on PSO-VMD-LSTM Q. Zhou et al.
30. FEASIBILITY OF USING GROUP METHOD OF DATA HANDLING (GMDH) APPROACH FOR HORIZONTAL COORDINATE TRANSFORMATION B. Kumi-Boateng & Y. Ziggah
31. Self-Healing Performance Assessment of Bacterial-Based Concrete Using Machine Learning Approaches X. Huang et al.
32. Predicting customer churn using grey wolf optimization‐based support vector machine with principal component analysis B. Durkaya Kurtcan & T. Ozcan
33. Prediction of Carbon Emission of the Transportation Sector in Jiangsu Province-Regression Prediction Model Based on GA-SVM Z. Huo et al.
34. Displacement Prediction of a Complex Landslide in the Three Gorges Reservoir Area (China) Using a Hybrid Computational Intelligence Approach J. Ma et al.
35. Gear fault diagnosis based on support vector machine optimized by artificial bee colony algorithm D. Yang et al.
36. Life-Cycle Performance Assessment and Distress Prediction of Subgrade Based on an Analytic Hierarchy Process and the PSO–LSSVM Model Q. Li et al.
37. Prediction of landslide displacement with dynamic features using intelligent approaches Y. Zhang et al.
38. Slope displacement prediction using sequential intelligent computing algorithms C. Liu et al.
39. Comparative study on credit card fraud detection based on different support vector machines C. Li et al.
40. Data Mining and Deep Learning for Predicting the Displacement of “Step-like” Landslides F. Miao et al.
41. Application of a two-step cluster analysis and the Apriori algorithm to classify the deformation states of two typical colluvial landslides in the Three Gorges, China X. Wu et al.
42. Utilization of Support Vector Models and Gene Expression Programming for Soil Strength Modeling A. Tenpe & A. Patel
43. Application of artificial intelligence in three aspects of landslide risk assessment: A comprehensive review R. He et al.
44. Integrating Data Modality and Statistical Learning Methods for Earthquake-Induced Landslide Susceptibility Mapping Z. Miao et al.
45. A hybrid machine learning and computing model for forecasting displacement of multifactor-induced landslides X. Zhu et al.
46. Input-parameter optimization using a SVR based ensemble model to predict landslide displacements in a reservoir area – A comparative study J. Zhang et al.
47. Application of Support Vector Machine Algorithm Incorporating Slime Mould Algorithm Strategy in Ancient Glass Classification Y. Guo et al.
48. A Cuckoo Search-Support Vector Machine Model for Predicting Dynamic Measurement Errors of Sensors M. Jiang et al.
49. The effectiveness of a drainage tunnel in increasing the rainfall threshold of a deep-seated landslide Z. Wei et al.
50. Estuary salinity prediction using a coupled GA-SVM model: a case study of the Min River Estuary, China Y. Fang et al.
51. A semantic information-driven stepwise landslide displacement prediction model F. Tang et al.
52. Suspended sediment yield estimation using genetic algorithm-based artificial intelligence models: case study of Mahanadi River, India A. Yadav et al.
53. Using color and 3D geometry features to segment fruit point cloud and improve fruit recognition accuracy G. Wu et al.
54. Automatic apple recognition based on the fusion of color and 3D feature for robotic fruit picking Y. Tao & J. Zhou
55. A novel hybrid algorithm with static and dynamic models for air quality index forecasting X. Zhao et al.
56. Toward the reliable prediction of reservoir landslide displacement using earthworm optimization algorithm-optimized support vector regression (EOA-SVR) Z. Liu et al.
57. Prediction of landslide displacement based on GA-LSSVM with multiple factors Z. Cai et al.
58. SVM‐based hybrid approach for corridor‐level travel‐time estimation R. Sharmila et al.
59. Landslide Susceptibility Mapping Using the Slope Unit for Southeastern Helong City, Jilin Province, China: A Comparison of ANN and SVM C. Yu & J. Chen
60. A FRAMEWORK FOR FINGERPRINT LIVENESS DETECTION USING SUPPORT VECTOR MACHINE OPTIMIZED BY GENETIC ALGORITHM Y. IBRAHIM et al.
61. Predicting the Deformation of a Slope Using a Random Coefficient Panel Data Model Z. Yuan et al.
62. Comparison of LR, 5-CV SVM, GA SVM, and PSO SVM for landslide susceptibility assessment in Tibetan Plateau area, China Y. Zhang et al.
63. Dynamic prediction of landslide life expectancy using ensemble system incorporating classical prediction models and machine learning L. Liu et al.
64. Modeling, evaluation and forecasting of suspended sediment load in Kal-e Shur River, Sabzevar Basin, in northeast of Iran M. Asadi et al.
65. 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.
66. Prediction of Slope Stability using Naive Bayes Classifier X. Feng et al.
67. A hybrid intelligent optimization approach to improving quality for serial multistage and multi-response coal preparation production systems X. Yin et al.
68. A review of models for water level forecasting based on machine learning W. Wee et al.
69. Metaheuristic-based support vector regression for landslide displacement prediction: a comparative study J. Ma et al.
70. Sea level prediction using climatic variables: a comparative study of SVM and hybrid wavelet SVM approaches S. Sithara et al.
71. Hierarchical perception guided deep learning framework for landslide detection with multi-source remotely sensed data C. Zhong et al.
72. Rainfall threshold for initiation of channelized debris flows in a small catchment based on in-site measurement Z. Wei et al.
73. Combining Numerical Simulation and Deep Learning for Landslide Displacement Prediction: An Attempt to Expand the Deep Learning Dataset W. Xu et al.
74. Improving the Landslide Susceptibility Prediction Accuracy by Using Genetic Algorithm Optimized Machine Learning Approach B. Zheng et al.
75. Intelligent optimization of Ti6Al4V alloy surface photolithography parameters via machine learning: A data-driven framework for precisionmanufacturing in industrial applications J. Lin et al.
76. 考虑注意力机制的新型深度学习模型预测滑坡位移 Z. Guo et al.
77. Prediction of Thermal Barrier Coatings Microstructural Features Based on Support Vector Machine Optimized by Cuckoo Search Algorithm D. Ye et al.
78. Determination of the shear failure areas of rock joints using a laser scanning technique and artificial intelligence algorithms Y. Ge et al.
79. Landslide Displacement Prediction Based on the VMD–TCN Hybrid Model C. Xu et al.
80. Dynamic measurement errors prediction for sensors based on firefly algorithm optimize support vector machine M. Jiang et al.
81. Assessment of circular-bored twin tunnel (CBTT) performance using soft computing methods H. Li et al.
82. Prediction of Slope Stability Based on Hybrid PSO and LSSVM X. Xue
83. Nonlinear Error Compensation of Capacitive Angular Encoders Based on Improved Particle Swarm Optimization Support Vector Machines B. Hou et al.
84. Predicting wave forces on coastal bridges using genetic algorithm enhanced ensemble learning framework G. Xu et al.
85. Statistical downscaling of sea levels: application of multi-criteria analysis for selection of global climate models S. Sithara et al.
86. An improved SVM web page classification algorithm X. Ren et al.
87. Estimating the refractive index of oxygenated and deoxygenated hemoglobin using genetic algorithm – support vector regression model I. Alade et al.
88. Random forests and evidential belief function-based landslide susceptibility assessment in Western Mazandaran Province, Iran H. Pourghasemi & N. Kerle
89. Prediction of Healing Performance of Autogenous Healing Concrete Using Machine Learning X. Huang et al.
90. Integration of Genetic Algorithm and Support Vector Machine to Predict Rail Track Degradation A. Falamarzi et al.
91. Application of time series analysis and PSO–SVM model in predicting the Bazimen landslide in the Three Gorges Reservoir, China C. Zhou et al.
92. Landslide Displacement Prediction Method Based on GA-Elman Model C. Wang et al.
93. A genetic algorithm-based support vector machine to estimate the transverse mixing coefficient in streams H. Nezaratian et al.
94. Quantitative prediction model and prewarning system of water yield capacity (WYC) from coal seam roof based on deep learning and joint advanced detection F. Dong et al.
95. Comparison of two optimized machine learning models for predicting displacement of rainfall-induced landslide: A case study in Sichuan Province, China X. Zhu et al.
96. Intelligent identification method for pipeline ultrasonic internal inspection X. Guangli et al.
97. Prediction and determination of mildew grade in grain storage based on FOA-SVM algorithm J. Yuan et al.
98. Introducing a novel multi-layer perceptron network based on stochastic gradient descent optimized by a meta-heuristic algorithm for landslide susceptibility mapping H. Hong et al.
99. Comparison of four kernel functions used in support vector machines for landslide susceptibility mapping: a case study at Suichuan area (China) H. Hong et al.
100. Discharge modeling and characteristic analysis of semi-circular side weir based on the soft computing method S. Li et al.
101. Landslide susceptibility mapping along the upper Jinsha River, south-western China: a comparison of hydrological and curvature watershed methods for slope unit classification X. Sun et al.
102. MUSEnet: High Temporal-Frequency Estimation of Landslide Deformation Field Through Joint InSAR and Hydrological Observations Using Deep Learning A. Guo et al.