Modeling Soil Water Retention Under Different Pressures Using Adaptive Neuro-Fuzzy Inference System
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DOI: 10.1007/s11269-023-03439-7
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- Mehrbakhsh Nilashi & Fausto Cavallaro & Abbas Mardani & Edmundas Kazimieras Zavadskas & Sarminah Samad & Othman Ibrahim, 2018. "Measuring Country Sustainability Performance Using Ensembles of Neuro-Fuzzy Technique," Sustainability, MDPI, vol. 10(8), pages 1-20, August.
- Zhongrong Zhang & Yiliao Song & Feng Liu & Jinpeng Liu, 2016. "Daily Average Wind Power Interval Forecasts Based on an Optimal Adaptive-Network-Based Fuzzy Inference System and Singular Spectrum Analysis," Sustainability, MDPI, vol. 8(2), pages 1-30, January.
- Tabbi Wilberforce & Abdul Ghani Olabi, 2020. "Performance Prediction of Proton Exchange Membrane Fuel Cells (PEMFC) Using Adaptive Neuro Inference System (ANFIS)," Sustainability, MDPI, vol. 12(12), pages 1-16, June.
- Reham Alhindawi & Yousef Abu Nahleh & Arun Kumar & Nirajan Shiwakoti, 2019. "Application of a Adaptive Neuro-Fuzzy Technique for Projection of the Greenhouse Gas Emissions from Road Transportation," Sustainability, MDPI, vol. 11(22), pages 1-17, November.
- Jinliang Zhang & YiMing Wei & Zhong-fu Tan & Wang Ke & Wei Tian, 2017. "A Hybrid Method for Short-Term Wind Speed Forecasting," Sustainability, MDPI, vol. 9(4), pages 1-10, April.
- Panapakidis, Ioannis P. & Dagoumas, Athanasios S., 2017. "Day-ahead natural gas demand forecasting based on the combination of wavelet transform and ANFIS/genetic algorithm/neural network model," Energy, Elsevier, vol. 118(C), pages 231-245.
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Keywords
Soil water retention; Pedotransfer Functions approach; Adaptive neuro-fuzzy inference systems; Field capacity; Permanent wilting point;All these keywords.
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