F. Salmasi

Water resources management · 2013–2020

A researcher in the Science corpus: 3 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Whom F. Salmasi trusts overall

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

1. John R. Koza
2. A. Johari
3. Vladimir Cherkassky
4. Michael Negnevitsky

Papers from F. Salmasi's perspective

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

1. Genetic Programming: On the Programming of Computers by Means of Natural Selection
2. The Nature Of Statistical Learning Theory
3. Neural network and genetic programming for modelling coastal algal blooms
4. Prediction of Soil-Water Characteristic Curve Using Genetic Programming
5. What Size Net Gives Valid Generalization?
6. Predicting discharge coefficient of compound broad-crested weir by using genetic programming (GP) and artificial neural network (ANN) techniques (Arabian Journal of Geosciences)
7. Back-propagation neural networks for modeling complex systems
8. Open Channel Flow
9. Artificial Intelligence: A Guide to Intelligent Systems
10. Forecasting of Multi-Step Ahead Reference Evapotranspiration Using Wavelet- Gaussian Process Regression Model (Water resources management)

Their papers

• Application of SVM, ANN, GRNN, RF, GP and RT models for predicting discharge coefficients of oblique sluice gates using experimental data (2020) — 56 citations
• Application of Gaussian Process Regression Model to Predict Discharge Coefficient of Gated Piano Key Weir (2019) — 58 citations
• Predicting discharge coefficient of compound broad-crested weir by using genetic programming (GP) and artificial neural network (ANN) techniques (2013) — 48 citations