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97 peer-reviewed articles • 13,830 peer-reviewed citations • Sorted by year • Download PDF (PDF by citations)
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1Deep learning and boosting framework for piping erosion susceptibility modeling: spatial evaluation of agricultural areas in the semi-arid region
Geocarto International, 2022, 37, 4628-4654
2.543Citations (PDF)
2Evaluation efficiency of hybrid deep learning algorithms with neural network decision tree and boosting methods for predicting groundwater potential
Geocarto International, 2022, 37, 5564-5584
2.5129Citations (PDF)
3Debris flows modeling using geo-environmental factors: developing hybridized deep-learning algorithms
Geocarto International, 2022, 37, 5150-5173
2.543Citations (PDF)
4Toward the development of deep learning analyses for snow avalanche releases in mountain regions
Geocarto International, 2022, 37, 7855-7880
2.544Citations (PDF)
5Uncertainty pattern in landslide susceptibility prediction modelling: Effects of different landslide boundaries and spatial shape expressions
Geoscience Frontiers, 2022, 13, 101317
8.4164Citations (PDF)
6Landslide susceptibility modeling based on remote sensing data and data mining techniques
Environmental Earth Sciences, 2022, 81,
2.124Citations (PDF)
7Regional rainfall-induced landslide hazard warning based on landslide susceptibility mapping and a critical rainfall threshold
Geomorphology, 2022, 408, 108236
2.2204Citations (PDF)
8Landslide susceptibility modeling based on GIS and ensemble techniques
Arabian Journal of Geosciences, 2022, 15,
0.97Citations (PDF)
9Flash flood susceptibility mapping using stacking ensemble machine learning models
Geocarto International, 2022, 37, 15010-15036
2.541Citations (PDF)
10Landslide susceptibility modeling based on ANFIS with teaching-learning-based optimization and Satin bowerbird optimizer
Geoscience Frontiers, 2021, 12, 93-107
8.4187Citations (PDF)
11GIS-based landslide susceptibility assessment using optimized hybrid machine learning methods
Catena, 2021, 196, 104833
4.3316Citations (PDF)
12Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility
Journal of Environmental Management, 2021, 284, 112015
6.3154Citations (PDF)
13Incorporating Landslide Spatial Information and Correlated Features among Conditioning Factors for Landslide Susceptibility Mapping
Remote Sensing, 2021, 13, 2166
2.759Citations (PDF)
14Hybrids of Support Vector Regression with Grey Wolf Optimizer and Firefly Algorithm for Spatial Prediction of Landslide Susceptibility
Remote Sensing, 2021, 13, 4966
2.729Citations (PDF)
15Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods
Science of the Total Environment, 2020, 701, 134979
5.6492Citations (PDF)
16GIS-Based Evaluation of Landslide Susceptibility Models Using Certainty Factors and Functional Trees-Based Ensemble Techniques
Applied Sciences (Switzerland), 2020, 10, 16
1.692Citations (PDF)
17Groundwater Spring Potential Mapping Using Artificial Intelligence Approach Based on Kernel Logistic Regression, Random Forest, and Alternating Decision Tree Models
Applied Sciences (Switzerland), 2020, 10, 425
1.6111Citations (PDF)
18Comparison of machine learning models for gully erosion susceptibility mapping
Geoscience Frontiers, 2020, 11, 1609-1620
8.4156Citations (PDF)
19An assessment of metaheuristic approaches for flood assessment
Journal of Hydrology, 2020, 582, 124536
5.075Citations (PDF)
20Performance Evaluation of GIS-Based Artificial Intelligence Approaches for Landslide Susceptibility Modeling and Spatial Patterns Analysis
ISPRS International Journal of Geo-Information, 2020, 9, 443
1.861Citations (PDF)
21Combining Evolutionary Algorithms and Machine Learning Models in Landslide Susceptibility Assessments
Remote Sensing, 2020, 12, 3854
2.7102Citations (PDF)
22Landslide Detection and Susceptibility Modeling on Cameron Highlands (Malaysia): A Comparison between Random Forest, Logistic Regression and Logistic Model Tree Algorithms
Forests, 2020, 11, 830
1.883Citations (PDF)
23Landslide Susceptibility Mapping Using Machine Learning Algorithms and Remote Sensing Data in a Tropical Environment
International Journal of Environmental Research and Public Health, 2020, 17, 4933
2.0156Citations (PDF)
24GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran
Remote Sensing, 2020, 12, 2478
2.7119Citations (PDF)
25Uncertainties Analysis of Collapse Susceptibility Prediction Based on Remote Sensing and GIS: Influences of Different Data-Based Models and Connections between Collapses and Environmental Factors
Remote Sensing, 2020, 12, 4134
2.752Citations (PDF)
26Performance Evaluation and Comparison of Bivariate Statistical-Based Artificial Intelligence Algorithms for Spatial Prediction of Landslides
ISPRS International Journal of Geo-Information, 2020, 9, 696
1.820Citations (PDF)
27Modeling Spatial Flood using Novel Ensemble Artificial Intelligence Approaches in Northern Iran
Remote Sensing, 2020, 12, 3423
2.779Citations (PDF)
28GIS-Based Gully Erosion Susceptibility Mapping: A Comparison of Computational Ensemble Data Mining Models
Applied Sciences (Switzerland), 2020, 10, 2039
1.6101Citations (PDF)
29Spatial Prediction of Landslide Susceptibility Based on GIS and Discriminant Functions
ISPRS International Journal of Geo-Information, 2020, 9, 144
1.868Citations (PDF)
30Landslide Susceptibility Evaluation and Management Using Different Machine Learning Methods in The Gallicash River Watershed, Iran
Remote Sensing, 2020, 12, 475
2.7221Citations (PDF)
31Hybrid Computational Intelligence Methods for Landslide Susceptibility Mapping
Symmetry, 2020, 12, 325
1.384Citations (PDF)
32Optimization of Computational Intelligence Models for Landslide Susceptibility Evaluation
Remote Sensing, 2020, 12, 2180
2.7143Citations (PDF)
33GIS-based evaluation of landslide susceptibility using hybrid computational intelligence models
Catena, 2020, 195, 104777
4.3231Citations (PDF)
34Spatial Prediction of Landslides Using Hybrid Integration of Artificial Intelligence Algorithms with Frequency Ratio and Index of Entropy in Nanzheng County, China
Applied Sciences (Switzerland), 2020, 10, 29
1.658Citations (PDF)
35Landslide Susceptibility Evaluation Using Hybrid Integration of Evidential Belief Function and Machine Learning Techniques
Water (Switzerland), 2020, 12, 113
2.096Citations (PDF)
36Gully Head-Cut Distribution Modeling Using Machine Learning Methods—A Case Study of N.W. Iran
Water (Switzerland), 2020, 12, 16
2.037Citations (PDF)
37Hybrid Computational Intelligence Models for Improvement Gully Erosion Assessment
Remote Sensing, 2020, 12, 140
2.744Citations (PDF)
38Evaluating the usage of tree-based ensemble methods in groundwater spring potential mapping
Journal of Hydrology, 2020, 583, 124602
5.0132Citations (PDF)
39Flash flood susceptibility modelling using functional tree and hybrid ensemble techniques
Journal of Hydrology, 2020, 587, 125007
5.0168Citations (PDF)
40Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran
Forests, 2020, 11, 421
1.8118Citations (PDF)
41Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms
International Journal of Environmental Research and Public Health, 2020, 17, 2749
2.0250Citations (PDF)
42Flood susceptibility mapping in Dingnan County (China) using adaptive neuro-fuzzy inference system with biogeography based optimization and imperialistic competitive algorithm
Journal of Environmental Management, 2019, 247, 712-729
6.3242Citations (PDF)
43A Hybrid Computational Intelligence Approach to Groundwater Spring Potential Mapping
Water (Switzerland), 2019, 11, 2013
2.081Citations (PDF)
44Spatial Prediction of Landslide Susceptibility Using GIS-Based Data Mining Techniques of ANFIS with Whale Optimization Algorithm (WOA) and Grey Wolf Optimizer (GWO)
Applied Sciences (Switzerland), 2019, 9, 3755
1.6162Citations (PDF)
45Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms
Science of the Total Environment, 2019, 663, 1-15
5.6236Citations (PDF)
46Groundwater spring potential mapping using population-based evolutionary algorithms and data mining methods
Science of the Total Environment, 2019, 684, 31-49
5.6130Citations (PDF)
47Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles
Journal of Hydrology, 2019, 575, 864-873
5.0294Citations (PDF)
48Novel Entropy and Rotation Forest-Based Credal Decision Tree Classifier for Landslide Susceptibility Modeling
Entropy, 2019, 21, 106
1.272Citations (PDF)
49Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree
Geocarto International, 2019, 34, 1177-1201
2.5122Citations (PDF)
50Spatial prediction of groundwater potentiality using ANFIS ensembled with teaching-learning-based and biogeography-based optimization
Journal of Hydrology, 2019, 572, 435-448
5.0192Citations (PDF)
51Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis
Natural Resources Research, 2019, 28, 1239-1258
4.0123Citations (PDF)
52Gully headcut susceptibility modeling using functional trees, naïve Bayes tree, and random forest models
Geoderma, 2019, 342, 1-11
5.0118Citations (PDF)
53A Novel Intelligence Approach of a Sequential Minimal Optimization-Based Support Vector Machine for Landslide Susceptibility Mapping
Sustainability, 2019, 11, 6323
2.351Citations (PDF)
54Applying population-based evolutionary algorithms and a neuro-fuzzy system for modeling landslide susceptibility
Catena, 2019, 172, 212-231
4.3257Citations (PDF)
55A Hybrid GIS Multi-Criteria Decision-Making Method for Flood Susceptibility Mapping at Shangyou, China
Remote Sensing, 2019, 11, 62
2.7160Citations (PDF)
56Spatial modelling of gully headcuts using UAV data and four best-first decision classifier ensembles (BFTree, Bag-BFTree, RS-BFTree, and RF-BFTree)
Geomorphology, 2019, 329, 184-193
2.279Citations (PDF)
57Landslide Susceptibility Modeling Using Integrated Ensemble Weights of Evidence with Logistic Regression and Random Forest Models
Applied Sciences (Switzerland), 2019, 9, 171
1.6159Citations (PDF)
58Study on recognition of mine water sources based on statistical analysis
Arabian Journal of Geosciences, 2019, 13,
0.912Citations (PDF)
59GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method
Catena, 2018, 164, 135-149
4.3252Citations (PDF)
60Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China
Science of the Total Environment, 2018, 626, 1121-1135
5.6448Citations (PDF)
61GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models
Science of the Total Environment, 2018, 634, 853-867
5.6334Citations (PDF)
62Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China
Science of the Total Environment, 2018, 625, 575-588
5.6404Citations (PDF)
63Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)
Catena, 2018, 163, 399-413
4.3473Citations (PDF)
64A novel ensemble approach of bivariate statistical-based logistic model tree classifier for landslide susceptibility assessment
Geocarto International, 2018, 33, 1398-1420
2.5106Citations (PDF)
65A comparative study on groundwater spring potential analysis based on statistical index, index of entropy and certainty factors models
Geocarto International, 2018, 33, 754-769
2.552Citations (PDF)
66Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution
Science of the Total Environment, 2018, 621, 1124-1141
5.6406Citations (PDF)
67Landslide Susceptibility Modeling Based on GIS and Novel Bagging-Based Kernel Logistic Regression
Applied Sciences (Switzerland), 2018, 8, 2540
1.6171Citations (PDF)
68Hybrid Integration Approach of Entropy with Logistic Regression and Support Vector Machine for Landslide Susceptibility Modeling
Entropy, 2018, 20, 884
1.283Citations (PDF)
69Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms
Sensors, 2018, 18, 2464
2.3163Citations (PDF)
70Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naïve Bayes tree for landslide susceptibility modeling
Science of the Total Environment, 2018, 644, 1006-1018
5.6473Citations (PDF)
71Novel hybrid artificial intelligence approach of bivariate statistical-methods-based kernel logistic regression classifier for landslide susceptibility modeling
Bulletin of Engineering Geology and the Environment, 2018, 78, 4397-4419
3.1159Citations (PDF)
72Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBFNetwork models for the Long County area (China)
Bulletin of Engineering Geology and the Environment, 2018, 78, 247-266
3.1161Citations (PDF)
73A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping
Geocarto International, 2017, 32, 367-385
2.5175Citations (PDF)
74GIS-based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naïve-Bayes tree, and alternating decision tree models
Geomatics, Natural Hazards and Risk, 2017, 8, 950-973
2.8217Citations (PDF)
75A hybrid fuzzy weight of evidence method in landslide susceptibility analysis on the Wuyuan area, China
Geomorphology, 2017, 290, 1-16
2.2145Citations (PDF)
76A comparative assessment between linear and quadratic discriminant analyses (LDA-QDA) with frequency ratio and weights-of-evidence models for forest fire susceptibility mapping in China
Arabian Journal of Geosciences, 2017, 10,
0.9116Citations (PDF)
77A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility
Catena, 2017, 151, 147-160
4.3885Citations (PDF)
78A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)
Environmental Earth Sciences, 2017, 76,
2.1144Citations (PDF)
79GIS-based spatial prediction of flood prone areas using standalone frequency ratio, logistic regression, weight of evidence and their ensemble techniques
Geomatics, Natural Hazards and Risk, 2017, 8, 1538-1561
2.8275Citations (PDF)
80Spatial prediction of rotational landslide using geographically weighted regression, logistic regression, and support vector machine models in Xing Guo area (China)
Geomatics, Natural Hazards and Risk, 2017, 8, 1997-2022
2.858Citations (PDF)
81A novel hybrid artificial intelligence approach based on the rotation forest ensemble and naïve Bayes tree classifiers for a landslide susceptibility assessment in Langao County, China
Geomatics, Natural Hazards and Risk, 2017, 8, 1955-1977
2.8191Citations (PDF)
82Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques
Geoderma, 2017, 305, 314-327
5.0371Citations (PDF)
83Comparison of four kernel functions used in support vector machines for landslide susceptibility mapping: a case study at Suichuan area (China)
Geomatics, Natural Hazards and Risk, 2017, 8, 544-569
2.8133Citations (PDF)
84A comparative study of landslide susceptibility maps produced using support vector machine with different kernel functions and entropy data mining models in China
Bulletin of Engineering Geology and the Environment, 2017, 77, 647-664
3.1192Citations (PDF)
85Prioritization of landslide conditioning factors and its spatial modeling in Shangnan County, China using GIS-based data mining algorithms
Bulletin of Engineering Geology and the Environment, 2017, 77, 611-629
3.1118Citations (PDF)
86Spatial prediction of landslide susceptibility using integrated frequency ratio with entropy and support vector machines by different kernel functions
Environmental Earth Sciences, 2016, 75,
2.152Citations (PDF)
87A GIS-based comparative study of frequency ratio, statistical index and weights-of-evidence models in landslide susceptibility mapping
Arabian Journal of Geosciences, 2016, 9,
0.9108Citations (PDF)
88Landslide susceptibility mapping based on GIS and support vector machine models for the Qianyang County, China
Environmental Earth Sciences, 2016, 75,
2.191Citations (PDF)
89Applying Information Theory and GIS-based quantitative methods to produce landslide susceptibility maps in Nancheng County, China
Landslides, 2016, 14, 1091-1111
4.2180Citations (PDF)
90A comparative study of statistical index and certainty factor models in landslide susceptibility mapping: a case study for the Shangzhou District, Shaanxi Province, China
Arabian Journal of Geosciences, 2015, 8, 9079-9088
0.935Citations (PDF)
91GIS-based assessment of landslide susceptibility using certainty factor and index of entropy models for the Qianyang County of Baoji city, China
Journal of Earth System Science, 2015, 124, 1399-1415
1.3128Citations (PDF)
92GIS-based landslide susceptibility mapping using analytical hierarchy process (AHP) and certainty factor (CF) models for the Baozhong region of Baoji City, China
Environmental Earth Sciences, 2015, 75,
2.1110Citations (PDF)
93Application of frequency ratio and weights of evidence models in landslide susceptibility mapping for the Shangzhou District of Shangluo City, China
Environmental Earth Sciences, 2015, 75,
2.1773Citations (PDF)
94Landslide susceptibility mapping based on GIS and information value model for the Chencang District of Baoji, China
Arabian Journal of Geosciences, 2014, 7, 4499-4511
0.9114Citations (PDF)
95Application 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, 2014, 8, 1829-1841
0.951Citations (PDF)
96Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy
Geocarto International, 0, , 1-16
2.5130Citations (PDF)
97Application of frequency ratio, weights of evidence and evidential belief function models in landslide susceptibility mapping
Geocarto International, 0, , 1-21
2.598Citations (PDF)