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Comparative evaluation of nearest neighbor and neural networks approach to estimate soil water retention at field capacity and permanent wilting point

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Title Comparative evaluation of nearest neighbor and neural networks approach to estimate soil water retention at field capacity and permanent wilting point
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Creator N. G. Patil , C. Mandal and D. K. Mandal
 
Subject Field capacity, K-nearest neighbor Algorithm , Neural regression, Pedotransfer function, Permanent Wilting point, Vertisols
 
Description Not Available
Evaluation of neural and k nearest neighbor (kNN) techniques of developing
pedotransfer functions (PTF) to predict soil water held at -33 kPa (Field Capacity
FC) and -1500 kPa (Permanent Wilting Point PWP) of Vertisols of India is
presented. Soil profile information of 26 representative sites comprising 157 soil
samples was used for PTF development. Four levels of input information were
used, (1) Textural data (data on sand, silt, and clay fraction-SSC), (2) Level 1+bulk
density data (SSCBD), (3) Level 2+organic matter (SSCBDOM), and (4) Level
1+organic matter (SSCOM), kNN PTFs predicted FC with greater accuracy
evidenced by lower root mean square error -RMSE (0.0695) compared to neural
PTFs (0.0775). Performance of neural PTFs exhibited improvement in RMSE
(from 0.076 to 0.0672) as the input variables increased. The performance of kNN
PTF was better (RMSE, 0.0315) than neural PTF using input level 1 (RMSE,
0.0402) to estimate PWP. At highest level of input, neural and kNN PTFs were
almost at par (RMSE, 0.0353 and 0.0358) in terms of prediction error. Better
prediction by kNN PTFs (FC/ PWP) with lowest input level (SSC) was significant
as accurate predictions were possible without more input. In general, kNN PTFs
showed advantage over neural PTFs
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Date 2024-07-01T11:04:52Z
2024-07-01T11:04:52Z
2013-11-01
 
Type Research Paper
 
Identifier N. G. Patil , C. Mandal and D. K. Mandal
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/83828
 
Language English
 
Relation Not Available;
 
Publisher Not Available