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Novel Genetic Algor...
Novel Genetic Algorithm (GA) based hybrid machine learning-pedotransfer Function (ML-PTF) for prediction of spatial pattern of saturated hydraulic conductivity
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- Singh, Vijay Kumar (författare)
- Faculty of Agriculture Science and Technology, Mahatma Gandhi Kashi Vidyapith, Varanasi, Uttar Pradesh, India
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- Panda, Kanhu Charan (författare)
- Department of Agricultural Engineering, Institute of Agricultural Sciences, BHU, Varanasi, Uttar Pradesh, India
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- Sagar, Atish (författare)
- Division of Agricultural Engineering, Indian Agricultural Research Institute, New Delhi, India
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- Al-Ansari, Nadhir, 1947- (författare)
- Luleå tekniska universitet,Geoteknologi
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- Duan, Huan-Feng (författare)
- Department of Civil and Environmental Engineering, Faculty of Construction and Environment, The Hong Kong Polytechnic University, Hong Kong
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- Paramaguru, Pradosh Kumar (författare)
- Production & Extension Management Division, ICAR-Indian Institute of Natural Resins and Gums, Ranchi, Jharkhand, India
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- Vishwakarma, Dinesh Kumar (författare)
- Department of Irrigation and Drainage Engineering, G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
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- Kumar, Ashish (författare)
- Department of Agricultural Engineering, Institute of Agricultural Sciences, BHU, Varanasi, Uttar Pradesh, India
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- Kumar, Devendra (författare)
- Department of Soil and Water Conservation Engineering, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
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- Kashyap, P. S. (författare)
- Department of Soil and Water Conservation Engineering, Govind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India
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- Singh, R. M. (författare)
- Department of Agricultural Engineering, Institute of Agricultural Sciences, BHU, Varanasi, Uttar Pradesh, India
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- Elbeltagi, Ahmed (författare)
- Agricultural Engineering Dept, Faculty of Agriculture, Mansoura University, Mansoura, Egypt
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(creator_code:org_t)
- 2022-05-10
- 2022
- Engelska.
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Ingår i: Engineering Applications of Computational Fluid Mechanics. - : Taylor & Francis. - 1994-2060 .- 1997-003X. ; 16:1, s. 1082-1099
- Relaterad länk:
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https://ltu.diva-por... (primary) (Raw object)
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- Saturated hydraulic conductivity (Ks) is an important soil characteristic that controls water moves through the soil. On the other hand, its measurement is difficult, time-consuming, and expensive; hence Pedotransfer Functions (PTFs) are commonly used for its estimation. Despite significant development over the years, the PTFs showed poor performance in predicting Ks. Using Genetic Algorithm (GA), two hybrid Machine Learning based PTFs (ML-PTF), i.e. a combination of GA with Multilayer Perceptron (MLP-GA) and Support Vector Machine (SVM-GA), were proposed in this study. We compared the performances of four machine learning algorithms for different sets of predictors. The predictor combination containing sand, clay, Field Capacity, and Wilting Point showed the highest accuracy for all the ML-PTFs. Among the ML-PTFs, the SVM-GA algorithm outperformed the rest of the PTFs. It was noticed that the SVM-GA PTF demonstrated higher efficiency than the MLP-GA algorithm. The reference model for hydraulic conductivity prediction was selected as the SVM-GA PTF paired with the K-5 predictor variables. The proposed PTFs were compared with 160 models from past literature. It was found that the algorithms advocated were an improvement over these PTFs. The current model would help in efficient spatio-temporal measurement of hydraulic conductivity using pre-available databases.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Samhällsbyggnadsteknik -- Geoteknik (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Civil Engineering -- Geotechnical Engineering (hsv//eng)
Nyckelord
- Hydraulic conductivity
- Pedotransfer Functions
- genetic algorithm
- Multilayer Perceptron
- support vector machine
- Geoteknik
- Soil Mechanics
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- ref (ämneskategori)
- art (ämneskategori)
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Singh, Vijay Kum ...
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Panda, Kanhu Cha ...
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Sagar, Atish
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Al-Ansari, Nadhi ...
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Duan, Huan-Feng
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Paramaguru, Prad ...
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Vishwakarma, Din ...
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Kumar, Ashish
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Kumar, Devendra
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Kashyap, P. S.
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Singh, R. M.
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Elbeltagi, Ahmed
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