World's Best Scientists 2026 revealed!

Overview

Haoyuan Hong is affiliated with Nanjing University of Information Science and Technology in China. Their research primarily focuses on Environmental Science, with a significant emphasis on Global and Planetary Change, Management, Monitoring, Policy and Law, Atmospheric Science, Safety, Risk, Reliability and Quality, and Water Science and Technology.

The main topics of their work include:

  • Landslides and related hazards
  • Flood Risk Assessment and Management
  • Cryospheric studies and observations
  • Geotechnical Engineering and Analysis
  • Hydrology and Drought Analysis
  • Hydrology and Watershed Management Studies
  • Tree Root and Stability Studies

Haoyuan Hong has contributed to several publications in prominent journals. Frequent publication venues include:

  • Journal of Environmental Management
  • Remote Sensing
  • Computers & Geosciences
  • Journal of Hydrology
  • The Science of The Total Environment

Recent papers authored or co-authored by Haoyuan Hong are:

  • "Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping" (2020, Computers & Geosciences)
  • "Predicting flood susceptibility using LSTM neural networks" (2020, Journal of Hydrology)
  • "Comparative study of landslide susceptibility mapping with different recurrent neural networks" (2020, Computers & Geosciences)
  • "A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping" (2020, International Journal of Geographical Information Systems)
  • "Modeling landslide susceptibility using LogitBoost alternating decision trees and forest by penalizing attributes with the bagging ensemble" (2020, The Science of The Total Environment)

Their frequent co-authors are:

  • Yi Wang
  • Wei Chen
  • Zhice Fang
  • Faming Huang
  • Ling Peng

Best Publications

  • A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

    Wei Chen;Xiaoshen Xie;Jiale Wang;Biswajeet Pradhan;Biswajeet Pradhan

  • A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods

    Khabat Khosravi;Himan Shahabi;Binh Thai Pham;Jan Adamowski

  • Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)

    Haoyuan Hong;Haoyuan Hong;Junzhi Liu;Junzhi Liu;Dieu Tien Bui;Biswajeet Pradhan;Biswajeet Pradhan

  • Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines

    Haoyuan Hong;Biswajeet Pradhan;Chong Xu;Dieu Tien Bui

  • Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China.

    Yi Wang;Zhice Fang;Haoyuan Hong;Haoyuan Hong

  • 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

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

    Haoyuan Hong;Hamid Reza Pourghasemi;Zohre Sadat Pourtaghi

  • Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China.

    Wei Chen;Jianbing Peng;Haoyuan Hong;Haoyuan Hong;Himan Shahabi

  • Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China.

    Haoyuan Hong;Paraskevas Tsangaratos;Ioanna Ilia;Junzhi Liu;Junzhi Liu

  • Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution.

    Haoyuan Hong;Haoyuan Hong;Mahdi Panahi;Ataollah Shirzadi;Tianwu Ma;Tianwu Ma

  • Application of alternating decision tree with AdaBoost and bagging ensembles for landslide susceptibility mapping

    Yanli Wu;Yutian Ke;Zhuo Chen;Shouyun Liang

  • Predicting flood susceptibility using long short-term memory (LSTM) neural network model

    Unknown

  • Multi-phase distribution of organic micropollutants in Xiamen Harbour, China

    JL Zhou;H Hong;Z Zhang;K Maskaoui

  • Analyzing urban spatial patterns and trend of urban growth using urban sprawl matrix: A study on Kolkata urban agglomeration, India

    Mehebub Sahana;Haoyuan Hong;Haoyuan Hong;Haroon Sajjad

  • Flood susceptibility mapping using convolutional neural network frameworks

    Yi Wang;Zhice Fang;Haoyuan Hong;Ling Peng

  • 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

  • GIS-based spatial prediction of flood prone areas using standalone frequency ratio, logistic regression, weight of evidence and their ensemble techniques

    Mahyat Shafapour Tehrany;Farzin Shabani;Mustafa Neamah Jebur;Haoyuan Hong

  • Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping

    Zhice Fang;Yi Wang;Ling Peng;Haoyuan Hong

  • GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method

    Wei Chen;Xiaoshen Xie;Jianbing Peng;Himan Shahabi

  • A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping

    Zhice Fang;Yi Wang;Ling Peng;Haoyuan Hong

  • A 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

    Wei Chen;Ataollah Shirzadi;Himan Shahabi;Baharin Bin Ahmad

  • Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy

    Haoyuan Hong;Wei Chen;Chong Xu;Ahmed M. Youssef

Frequent Co-Authors

A-Xing Zhu
A-Xing Zhu University of Wisconsin–Madison
Biswajeet Pradhan
Biswajeet Pradhan University of Technology Sydney
Dieu Tien Bui
Dieu Tien Bui University of South-Eastern Norway
Chong Xu
Chong Xu China Earthquake Administration
Himan Shahabi
Himan Shahabi University of Kurdistan
Ataollah Shirzadi
Ataollah Shirzadi University of Kurdistan
Baharin Bin Ahmad
Baharin Bin Ahmad University of Technology Malaysia
Hamid Reza Pourghasemi
Hamid Reza Pourghasemi Shiraz University
John L. Zhou
John L. Zhou University of Technology Sydney
Minhan Dai
Minhan Dai Xiamen University

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