序号
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论文标题
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来源
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我校作者
及单位
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研究领域
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1
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A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping(高被引)
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GEOCARTO INT 32 (4): 367-385 2017
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陈伟
地环
第一作者
|
地球科学
|
2
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A comparative study of landslide susceptibility maps produced using support vector machine with different kernel functions and entropy data mining models in China(高被引)
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BULL ENG GEOL ENVIRON 77 (2): 647-664 MAY 2018
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陈伟
地环
第一作者
|
地球科学
|
3
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Spatial prediction of landslide susceptibility using an adaptive neuro-fuzzy inference system combined with frequency ratio, generalized additive model, and support vector machine techniques(高被引)(热点)
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GEOMORPHOLOGY 297: 69-85 NOV 15 2017
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陈伟
地环
第一作者
|
地球科学
|
4
|
GIS-based landslide susceptibility modelling: a comparative assessment of kernel logistic regression, Naive-Bayes tree, and alternating decision tree models(高被引)
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GEOMAT NAT HAZARDS RISK 8 (2): 950-973 2017
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陈伟
地环
第一作者
|
地球科学
|
5
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Prioritization of landslide conditioning factors and its spatial modeling in Shangnan County, China using GIS-based data mining algorithms(高被引)
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BULL ENG GEOL ENVIRON 77 (2): 611-629 MAY 2018
|
陈伟
地环
第一作者
|
地球科学
|
6
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A novel ensemble approach of bivariate statistical-based logistic model tree classifier for landslide susceptibility assessment(高被引)(热点)
|
GEOCARTO INT 33 (12): 1398-1420 DEC 2 2018
|
陈伟
地环
第一作者
|
地球科学
|
7
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Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBFNetwork models for the Long County area (China)(高被引)(热点)
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BULL ENG GEOL ENVIRON 78 (1): 247-266 FEB 2019
|
陈伟
地环
第一作者
|
地球科学
|
8
|
Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy(高被引)
|
GEOCARTO INT 32 (2): 139-154 2017
|
陈伟
地环
合作作者
|
地球科学
|
9
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Landslide Detection and Susceptibility Mapping by AIRSAR Data Using Support Vector Machine and Index of Entropy Models in Cameron Highlands, Malaysia(热点)
|
REMOTE SENS 10 (10): - OCT 2018
|
陈伟
地环
合作作者
|
地球科学
|
10
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Hyperspectral Image Classification by Nonlocal Joint Collaborative Representation With a Locally Adaptive Dictionary(高被引)
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IEEE TRANS GEOSCI REMOT SEN 52 (6): 3707-3719 JUN 2014
|
黄远程
测绘
合作作者
|
地球科学
|
11
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A Nonlocal Weighted Joint Sparse Representation Classification Method for Hyperspectral Imagery(高被引)
|
IEEE J SEL TOP APPL EARTH OBS 7 (6): 2056-2065 SP. ISS. SI JUN 2014
|
黄远程
测绘
合作作者
|
地球科学
|
12
|
Geochemical and mineralogical evidence for a coal-hosted uranium deposit in the Yili Basin, Xinjiang, northwestern China(高被引)
|
ORE GEOL REV 70: 1-30 OCT 2015
|
杨建业
材料
合作作者
|
地球科学
|
13
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A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility(高被引)(热点)
|
CATENA 151: 147-160 APR 2017
|
陈伟
地环
第一作者
|
农业科学
|
14
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Performance evaluation of GIS-based new ensemble data mining techniques of adaptive neuro-fuzzy inference system (ANFIS) with genetic algorithm (GA), differential evolution (DE), and particle swarm optimization (PSO) for landslide spatial modelling(高被引)(热点)
|
CATENA 157: 310-324 OCT 2017
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陈伟
地环
第一作者
|
农业科学
|
15
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Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques(高被引)
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GEODERMA 305: 314-327 NOV 1 2017
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陈伟
地环
第一作者
|
农业科学
|
16
|
GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method(高被引)(热点)
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CATENA 164: 135-149 MAY 2018
|
陈伟
地环
第一作者
|
农业科学
|
17
|
Applying population-based evolutionary algorithms and a neuro-fuzzy system for modeling landslide susceptibility(高被引)(热点)
|
CATENA 172: 212-231 JAN 2019
|
陈伟
地环
第一作者
|
农业科学
|
18
|
Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)(高被引)
|
CATENA 163: 399-413 APR 2018
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陈伟 地环
合作作者
|
农业科学
|
19
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Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China(高被引)(热点)
|
SCI TOTAL ENVIR 626: 1121-1135 JUN 1 2018
|
陈伟
地环
第一作者
|
环境科学与生态学
|
20
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Performance evaluation of the GIS-based data mining techniques of best-first decision tree, random forest, and naive Bayes tree for landslide susceptibility modeling(高被引)(热点)
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SCI TOTAL ENVIR 644: 1006-1018 DEC 10 2018
|
陈伟
地环
第一作者
|
环境科学与生态学
|
21
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Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution(高被引)
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SCI TOTAL ENVIR 621: 1124-1141 APR 15 2018
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陈伟
地环
合作作者
|
环境科学与生态学
|
22
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Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China(高被引)
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SCI TOTAL ENVIR 625: 575-588 JUN 1 2018
|
陈伟 地环
合作作者
|
环境科学与生态学
|
23
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GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models(高被引)
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SCI TOTAL ENVIR 634: 853-867 SEP 1 2018
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陈伟
地环
第一作者
|
环境科学与生态学
|
24
|
Numerical study on the pipe flow characteristics of the cemented paste backfill slurry considering hydration effects(高被引)
|
POWDER TECHNOL 343: 454-464 FEB 1 2019
|
刘浪
能源
第一作者
|
化学
|
25
|
Systematic Research on the Application of Steel Slag Resources under the Background of Big Data(高被引)(热点)
|
COMPLEXITY : - 2018
|
康乐
材料
第一作者
|
数学
|
26
|
Optimization on fresh outdoor air ratio of air conditioning system with stratum ventilation for both targeted indoor air quality and maximal energy saving(高被引)
|
BLDG ENVIRON 147: 11-22 JAN 2019
|
郇超
能源
合作作者
|
工程学
|
27
|
Equivalent room air temperature based cooling load estimation method for stratum ventilation and displacement ventilation(高被引)
|
BLDG ENVIRON 148: 67-81 JAN 15 2019
|
郇超
能源
合作作者
|
工程学
|
28
|
Enhanced Structural Stability of Nickel-Cobalt Hydroxide via Intrinsic Pillar Effect of Metaborate for High-Power and Long-Life Supercapacitor Electrodes(高被引)
|
NANO LETT 17 (1): 429-436 JAN 2017
|
李赛
化工
合作作者
|
材料科学
|
29
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Unravelling surface and interfacial structures of a metal-organic framework by transmission electron microscopy(高被引)
|
NAT MATER 16 (5): 532-+ MAY 2017
|
郑斌
材料
合作作者
|
材料科学
|