A. Rahimikhoob
Environmental Engineering · 2013–2014
A researcher in the Science corpus: 2 papers; trusts 11 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Environmental Engineering — 7 citations into it; #2,166 of 5,479 by trust here, #4,694 by citations
- Global and Planetary Change — 7 citations into it; #3,133 of 10,225 by trust here, #6,997 by citations
- Water Science and Technology — 7 citations into it; #403 of 1,711 by trust here, #1,062 by citations
Whom A. Rahimikhoob trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Dimitri P. Solomatine
- J. Ross Quinlan
- Lutz Prechelt
- B. Bhattacharya
- Suat Irmak
- Yunpeng Xue
- R. G. Allen
- M. Taghi Sattari
- Narendra Singh Raghuwanshi
- Kurt Hornik
Who trusts A. Rahimikhoob overall
- Behrooz Keshtegar
- Ozgur Kisi
- Zhenliang Yin
- Ravinesh C. Deo
- Hamed Ghohani Arab
- Xiaohu Wen
- Mohammad Zounemat‐Kermani
- Qi Feng
Papers from A. Rahimikhoob's perspective
Ordered by how strongly the researchers A. Rahimikhoob trusts endorse each paper. Same corpus, a different order for every researcher.
- Learning With Continuous Classes
- M5 Model Trees and Neural Networks: Application to Flood Forecasting in the Upper Reach of the Huai River in China
- Multilayer feedforward networks are universal approximators
- Daily Grass and Alfalfa-Reference Evapotranspiration Estimates and Alfalfa-to-Grass Evapotranspiration Ratios in Florida
- Comparing Penman-Monteith and Priestley-Taylor approaches as reference-evapotranspiration inputs for modeling maize water-use under Mediterranean conditions
- Estimating Evapotranspiration using Artificial Neural Network
- Data Mining Practical Machine Learning Tools And Techniques With Java Implementations
- Neural networks and M5 model trees in modelling water level-discharge relationship (Neurocomputing)
- Daily reservoir inflow forecasting using artificial neural networks with stopped training approach
- Automatic early stopping using cross validation: quantifying the criteria
Their papers
- Comparison between M5 Model Tree and Neural Networks for Estimating Reference Evapotranspiration in an Arid Environment (2014) — 74 citations
- A Comparison Between Conventional and M5 Model Tree Methods for Converting Pan Evaporation to Reference Evapotranspiration for Semi-Arid Region (2013) — 91 citations