Letter to the editor “Estimation of sodium adsorption ratio indicator using data mining methods: a case study in Urmia Lake basin, Iran” by Mohammad Taghi Sattari, Arya Farkhondeh, and John Patrick Abraham
- 47 Downloads
The abilities of artificial intelligence techniques such as artificial neural networks (ANN) and Support Vector Regression (SVM) today have been well documented in engineering sciences (Buyukyildiz et al. 2014; Fahimi et al. 2017; Kim and Seo 2015; Moazenzadeh et al. 2018; Emamgholizadeh et al. 2018). These methods can perfectly model complex and nonlinear structures, as well as with high processing power and quick computations in engineering sciences (Moazenzadeh et al. 2018; Swenson and Wahr 2006; Holmes et al. 2005; Zhang et al. 2003). Research on these method can be usefully provided that a research (original paper) helps other researchers around the world when finding a research for other researchers that the details of the research and the process of work will be transparent to everyone, especially in the case of highly sensitive artificial intelligence and a small change in the parameters of these models can change the result of the research. In this discussion,...
- Swenson S, Wahr J (2006) Post-processing removal of correlated errors in GRACE data. Geophys Res Lett 33(8). https://doi.org/10.1029/2005GL025285