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Xiaojing Wang
Researcher at Xi'an University of Science and Technology
Publications - 10
Citations - 1063
Xiaojing Wang is an academic researcher from Xi'an University of Science and Technology. The author has contributed to research in topics: Topographic Wetness Index & Support vector machine. The author has an hindex of 8, co-authored 9 publications receiving 586 citations.
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Journal ArticleDOI
Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods.
Wei Chen,Yang Li,Weifeng Xue,Himan Shahabi,Shaojun Li,Haoyuan Hong,Haoyuan Hong,Xiaojing Wang,Huiyuan Bian,Shuai Zhang,Biswajeet Pradhan,Baharin Bin Ahmad +11 more
TL;DR: The results indicated that the RF method is an efficient and reliable model in flood susceptibility assessment, with the highest AUC values, positive predictive rate, negative predictive rates, specificity, and accuracy for the training and validation datasets.
Journal ArticleDOI
Flood susceptibility modelling using novel hybrid approach of reduced-error pruning trees with bagging and random subspace ensembles
Wei Chen,Wei Chen,Haoyuan Hong,Haoyuan Hong,Shaojun Li,Himan Shahabi,Yi Wang,Xiaojing Wang,Baharin Bin Ahmad +8 more
TL;DR: In this article, the authors employ machine learning-based Reduced Error Pruning Trees (REPTree) with Bagging (Bag-REPTrees) and Random Subspace (RS-REptree) ensemble frameworks for spatial prediction of flood susceptibility using a geographic information system (GIS).
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Landslide spatial modelling using novel bivariate statistical based Naïve Bayes, RBF Classifier, and RBF Network machine learning algorithms
Qingfeng He,Himan Shahabi,Ataollah Shirzadi,Shaojun Li,Wei Chen,Nianqin Wang,Huichan Chai,Huiyuan Bian,Jianquan Ma,Yingtao Chen,Xiaojing Wang,Kamran Chapi,Baharin Bin Ahmad +12 more
TL;DR: The obtained results pointed out that the RBF Classifier model is a promising method for spatial prediction of landslide over the world.
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Landslide Susceptibility Modeling Based on GIS and Novel Bagging-Based Kernel Logistic Regression
Wei Chen,Himan Shahabi,Shuai Zhang,Khabat Khosravi,Ataollah Shirzadi,Kamran Chapi,Binh Thai Pham,Tingyu Zhang,Lingyu Zhang,Huichan Chai,Jianquan Ma,Yingtao Chen,Xiaojing Wang,Renwei Li,Baharin Bin Ahmad +14 more
TL;DR: The findings overall confirmed that a combination of the meta model with a decision tree classifier based on a functional algorithm can decrease the over-fitting and variance problems of data, which could enhance the prediction power of the landslide model.
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Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree
Wei Chen,Xia Zhao,Himan Shahabi,Ataollah Shirzadi,Khabat Khosravi,Huichan Chai,Shuai Zhang,Lingyu Zhang,Jianquan Ma,Yingtao Chen,Xiaojing Wang,Baharin Bin Ahmad,Renwei Li +12 more
TL;DR: In this article, a hybrid of evidence belief function (EBF) with logistic regression and logistic model tree was used for landslide susceptibility modeling. And the performance of three models was evaluated using the area under the curve (AUC).