Using random forest for the risk assessment of coal-floor water inrush in Panjiayao Coal Mine, northern China

An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction

(2017) Oluwarotimi Williams Samuel et al.   EXPERT SYSTEMS WITH APPLICATIONS

Method for assessing coal-floor water-inrush risk based on the variable-weight model and unascertained measure theory

(2017) Qiang Wu et al.   HYDROGEOLOGY JOURNAL

Vulnerability assessment of water bursting from Ordovician limestone into coal mines of China

(2016) Yifan Zeng et al.   Environmental Earth Sciences

Landslide susceptibility assessment in Lianhua County (China): A comparison between a random forest data mining technique and bivariate and multivariate statistical models

(2016) Haoyuan Hong et al.   GEOMORPHOLOGY

Evaluation of four supervised learning methods for groundwater spring potential mapping in Khalkhal region (Iran) using GIS-based features

(2016) Seyed Amir Naghibi et al.   HYDROGEOLOGY JOURNAL

A probabilistic neural network based approach for predicting the output power of wind turbines

(2016) Sajad Tabatabaei   JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE

Method for prediction of landslide movements based on random forests

(2016) Martin Krkač et al.   Landslides

Assessment of Water Inrush Risk Using the Fuzzy Delphi Analytic Hierarchy Process and Grey Relational Analysis in the Liangzhuang Coal Mine, China

(2016) Mei Qiu et al.   Mine Water and the Environment

Using an unsupervised approach of Probabilistic Neural Network (PNN) for land use classification from multitemporal satellite images

(2015) Jawad Iounousse et al.   APPLIED SOFT COMPUTING

Crop classification of upland fields using Random forest of time-series Landsat 7 ETM+ data

(2015) Kenichi Tatsumi et al.   COMPUTERS AND ELECTRONICS IN AGRICULTURE

Land cover mapping based on random forest classification of multitemporal spectral and thermal images

(2015) Vahid Eisavi et al.   ENVIRONMENTAL MONITORING AND ASSESSMENT

Flood hazard risk assessment model based on random forest

(2015) Zhaoli Wang et al.   JOURNAL OF HYDROLOGY

Evaluation and zoning of groundwater hazards in Pingshuo No. 1 underground coal mine, Shanxi Province, China

(2014) Qiang Wu et al.   HYDROGEOLOGY JOURNAL

Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers

(2014) Elhadi Adam et al.   INTERNATIONAL JOURNAL OF REMOTE SENSING

An Attribute Synthetic Evaluation System for Risk Assessment of Floor Water Inrush in Coal Mines

(2014) L. P. Li et al.   Mine Water and the Environment

Quantitative credit risk assessment using support vector machines: Broad versus Narrow default definitions

(2013) Terry Harris   EXPERT SYSTEMS WITH APPLICATIONS

A study on a water-inrush incident at Laohutai coalmine

(2013) Tie Li et al.   INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES

Predicting carcinogenicity of diverse chemicals using probabilistic neural network modeling approaches

(2013) Kunwar P. Singh et al.   TOXICOLOGY AND APPLIED PHARMACOLOGY

Application of the Analytic Hierarchy Process to Assessment of Water Inrush: A Case Study for the No. 17 Coal Seam in the Sanhejian Coal Mine, China

(2013) Qiang Wu et al.   Mine Water and the Environment

A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

(2012) Biswajeet Pradhan   COMPUTERS & GEOSCIENCES

A geological assessment method of floor water inrush risk and its application

(2012) Zhaoping Meng et al.   ENGINEERING GEOLOGY

Risk assessment of floor water inrush in coal mines based on secondary fuzzy comprehensive evaluation

(2012) Yi Wang et al.   INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES

Avoiding Coal–Water Conflicts During the Development of China’s Large Coal-Producing Regions

(2012) Wenjie Sun et al.   Mine Water and the Environment

Overview of random forest methodology and practical guidance with emphasis on computational biology and bioinformatics

(2012) Anne-Laure Boulesteix et al.   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

An assessment of the effectiveness of a random forest classifier for land-cover classification

(2011) V.F. Rodriguez-Galiano et al.   ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING

Prediction of Floor Water Inrush: The Application of GIS-Based AHP Vulnerable Index Method to Donghuantuo Coal Mine, China

(2011) Qiang Wu et al.   ROCK MECHANICS AND ROCK ENGINEERING

Classification and regression trees

(2011) Wei-Yin Loh   Wiley Interdisciplinary Reviews-Data Mining and Knowledge Discovery

A fuzzy random forest

(2010) Piero Bonissone et al.   INTERNATIONAL JOURNAL OF APPROXIMATE REASONING

Variable Importance Assessment in Regression: Linear Regression versus Random Forest

(2009) Ulrike Grömping   AMERICAN STATISTICIAN

A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

(2009) Bjoern H Menze et al.   BMC BIOINFORMATICS

Application of Random Forest Approach to QSAR Prediction of Aquatic Toxicity

(2009) Pavel G. Polishchuk et al.   Journal of Chemical Information and Modeling

Prediction of groundwater inrush into coal mines from aquifers underlying the coal seams in China: application of vulnerability index method to Zhangcun Coal Mine, China

(2008) Qiang Wu et al.   Environmental geology.

Prediction of groundwater inrush into coal mines from aquifers underlying the coal seams in China: vulnerability index method and its construction

(2008) Qiang Wu et al.   Environmental geology.