Using of hybrid fuzzy models to predict spatiotemporal groundwater quality parameters
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
http://link.springer.com/content/pdf/10.1007/s12145-015-0222-6.pdf
Reference22 articles.
1. Adamowski J, Chan HF (2011) A wavelet neural network conjunction model for groundwater level forecasting. J Hydrol 407:28–40
2. ASCE Task Committee on Application of Artificial Neural Networks in Hydrology (2000) Artificial Neural Networks in Hydrology. I: Preliminary Concepts. J Hydrol Eng ASCE 5(2):115–123
3. Bashir ZA, El-Hawary ME (2009) Applying wavelets to short-term load forecasting using PSO-based neural networks. IEEE Trans Power Syst 24(1):20–7
4. Chiu SL (1994) Fuzzy model identification based on cluster estimation. J Intell Fuzzy Syst 2:267–278
5. Dixon B (2005) Applicability of neuro-fuzzy techniques in predicting ground-water vulnerability: a GIS-based sensitivity analysis. J Hydrol 309:17–38
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