Wenyan Wu

Environmental Engineering · 2014

A researcher in the Science corpus: 1 paper; trusts 18 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Environmental Engineering — 20 citations into it; #3,953 of 5,479 by trust here, #4,694 by citations
• Water Science and Technology — 16 citations into it; #1,099 of 1,711 by trust here, #1,442 by citations
• Artificial Intelligence — 12 citations into it
• Electrical and Electronic Engineering — 5 citations into it
• Global and Planetary Change — 5 citations into it

Whom Wenyan Wu trusts overall

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

1. Holger R. Maier
2. Gavin J. Bowden
3. Soteris A. Kalogirou
4. Ashish Sharma
5. Graeme C. Dandy
6. Stefano Galelli
7. Julian D. Olden
8. Jens Christian Refsgaard
9. C. Dawson
10. Saman Razavi

Who trusts Wenyan Wu overall

1. Sheen Mclean Cabaneros
2. Yingyi Chen
3. John Kaiser Calautit
4. Lihua Song

Papers from Wenyan Wu's perspective

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

1. Neural networks for the prediction and forecasting of water resource variables: a review of modelling issues and applications (Environmental Modelling & Software)
2. Ten iterative steps in development and evaluation of environmental models (Environmental Modelling & Software)
3. Seasonal to interannual rainfall probabilistic forecasts for improved water supply management: Part 1 — A strategy for system predictor identification
4. Modelling guidelinesterminology and guiding principles
5. Methods used for the development of neural networks for the prediction of water resource variables in river systems: Current status and future directions (Environmental Modelling & Software)
6. Input determination for neural network models in water resources applications. Part 1—background and methodology
7. HydroTest: A web-based toolbox of evaluation metrics for the standardised assessment of hydrological forecasts (Environmental Modelling & Software)
8. Numerical assessment of metamodelling strategies in computationally intensive optimization
9. Illuminating the “black box”: a randomization approach for understanding variable contributions in artificial neural networks
10. Review of the self-organizing map (SOM) approach in water resources: Analysis, modelling and application (Environmental Modelling & Software)

Their papers

• Protocol for developing ANN models and its application to the assessment of the quality of the ANN model development process in drinking water quality modelling (2014) — 317 citations