Lin-shan Yang

Environmental Engineering · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 23 citations into it
• Global and Planetary Change — 21 citations into it
• Water Science and Technology — 17 citations into it
• Artificial Intelligence — 11 citations into it
• Electrical and Electronic Engineering — 8 citations into it

Whom Lin-shan Yang trusts overall

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

1. Ozgur Kisi
2. Ravinesh C. Deo

Papers from Lin-shan Yang's perspective

Ordered by how strongly the researchers Lin-shan Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. The Nature of Statistical Learning Theory
2. Model Induction with Support Vector Machines: Introduction and Applications
3. Two hybrid Artificial Intelligence approaches for modeling rainfall–runoff process
4. A wavelet-support vector machine conjunction model for monthly streamflow forecasting
5. Learning With Continuous Classes
6. Forecasting Evaporative Loss by Least-Square Support-Vector Regression and Evaluation with Genetic Programming, Gaussian Process, and Minimax Probability Machine Regression: Case Study of Brisbane…
7. Wavelet support vector machine (IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics))
8. Artificial intelligence based models for stream-flow forecasting: 2000-2015
9. Stream-flow forecasting using extreme learning machines: a case study in a semi-arid region in Iraq
10. Multivariate adaptive regression splines

Their papers

• Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment (2018) — 54 citations
• Integrating genetic algorithm and support vector machine for modeling daily reference evapotranspiration in a semi-arid mountain area (2017) — 64 citations