Novel Genetic Algorithm (GA) based hybrid machine learning-pedotransfer Function (ML-PTF) for prediction of spatial pattern of saturated hydraulic conductivity-Reference-Cited by-同舟云学术

Novel Genetic Algorithm (GA) based hybrid machine learning-pedotransfer Function (ML-PTF) for prediction of spatial pattern of saturated hydraulic conductivity

Published:2022-05-10 Issue:1 Volume:16 Page:1082-1099
ISSN:1994-2060
Container-title:Engineering Applications of Computational Fluid Mechanics
language:en
Short-container-title:Engineering Applications of Computational Fluid Mechanics

Author:

Singh Vijay Kumar¹,Panda Kanhu Charan²,Sagar Atish³,Al-Ansari Nadhir⁴,Duan Huan-Feng⁵,Paramaguru Pradosh Kumar⁶,Vishwakarma Dinesh Kumar⁷,Kumar Ashish²,Kumar Devendra⁸,Kashyap P. S.⁸,Singh R. M.²,Elbeltagi Ahmed⁹^ORCID

Affiliation:

1. Faculty of Agriculture Science and Technology, Mahatma Gandhi Kashi Vidyapith, Varanasi, Uttar Pradesh, India

2. Department of Agricultural Engineering, Institute of Agricultural Sciences, BHU, Varanasi, Uttar Pradesh, India

3. Division of Agricultural Engineering, Indian Agricultural Research Institute, New Delhi, India

4. Department of Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, Lulea, Sweden

5. Department of Civil and Environmental Engineering, Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hong Kong

6. Production & Extension Management Division, ICAR-Indian Institute of Natural Resins and Gums, Ranchi, Jharkhand, India

7. Department of Irrigation and Drainage Engineering, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India

8. Department of Soil and Water Conservation Engineering, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India

9. Agricultural Engineering Dept, Faculty of Agriculture, Mansoura University, Mansoura, Egypt

Publisher

Informa UK Limited

Subject

Modeling and Simulation,General Computer Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/19942060.2022.2071994

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4. Toward reliable model for prediction Drilling Fluid Density at wellbore conditions: A LSSVM model

5. A LSSVM approach for determining well placement and conning phenomena in horizontal wells

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