P. Indra

Management, Monitoring, Policy and Law · 2017

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Management, Monitoring, Policy and Law — 18 citations into it; #2,139 of 2,821 by trust here, #1,064 by citations
• Global and Planetary Change — 12 citations into it; #7,723 of 10,225 by trust here, #5,068 by citations
• Safety, Risk, Reliability and Quality — 10 citations into it
• Mechanical Engineering — 6 citations into it; #6,482 of 8,300 by trust here, #4,521 by citations
• Artificial Intelligence — 5 citations into it

Whom P. Indra trusts overall

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

1. Biswajeet Pradhan
2. Isik Yilmaz
3. João Gama

Who trusts P. Indra overall

1. Binh Thai Pham

Papers from P. Indra's perspective

Ordered by how strongly the researchers P. Indra 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 mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat - Turkey) (Computational Geosciences)
3. Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression (Landslides)
4. Artificial neural networks: fundamentals, computing, design, and application.
5. Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines
6. Application of an evidential belief function model in landslide susceptibility mapping (Computational Geosciences)
7. Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naïve Bayes Models
8. Data Mining Practical Machine Learning Tools and Techniques
9. A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS (Computational Geosciences)
10. Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

Their papers

• Landslide susceptibility assesssment in the Uttarakhand area (India) using GIS: a comparison study of prediction capability of naïve bayes, multilayer perceptron neural networks, and functional trees methods (2017) — 364 citations