Jianquan Ma

Management, Monitoring, Policy and Law · 2017–2019

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Management, Monitoring, Policy and Law — 33 citations into it
• Global and Planetary Change — 26 citations into it
• Mechanical Engineering — 14 citations into it

Whom Jianquan Ma trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Biswajeet Pradhan (in Management, Monitoring, Policy and Law)

Papers from Jianquan Ma's perspective

Ordered by how strongly the researchers Jianquan Ma trusts endorse each paper. Same corpus, a different order for every researcher.

1. Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran (Proceedings of the Indian Academy of Sciences, Earth and Planetary Sciences)
2. Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China. (Science of the Total Environment)
3. Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat - Turkey) (Computational Geosciences)
4. Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic… (Landslides)
5. Data Mining Practical Machine Learning Tools and Techniques
6. Landslide susceptibility mapping : A comparison of logistic regression and neural networks methods in a medium scale study, Hendek Region (Turkey)
7. Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines
8. Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS
9. Delineation of landslide hazard areas on Penang Island, Malaysia, by using frequency ratio, logistic regression, and artificial neural network models
10. GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method

Their papers

• Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree (2019) — 121 citations
• A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility (2017) — 836 citations