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A new simulation approach of genetic programming in modelling of soil water retention property of unsaturated soil

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Title A new simulation approach of genetic programming in modelling of soil water retention property of unsaturated soil
 
Creator GARG, A
GARG, A
ZHOU, WH
TAI, K
DEO, MC
 
Subject MULTIPLE ROBOTIC MANIPULATORS
ARTIFICIAL NEURAL-NETWORKS
PARTICLE-SIZE DISTRIBUTION
HYDRAULIC CONDUCTIVITY
BULK-DENSITY
FORMULATION
PREDICTION
SYSTEMS
STRESS
CURVES
Simulation
Modelling
Soil characteristics
Soil water retention curves
 
Description Purpose - For measuring the effect of crop root content on soil water retention curves (SWRC), a simulation approach (multi-gene genetic programming (MGGP)), which develops the model structure and its coefficients automatically can be applied. However, it does not perform well due to two vital issues related to its generalization: inappropriate formulation procedure of the multi-gene model and the difficulty in model selection. The purpose of this paper is to propose a heuristic-based-MGGP (N-MGGP) to formulate the functional relationship between the water content and two input parameters (soil suction and volumetric crop root content). Design/methodology/approach - A new simulation approach (heuristic-based-MGGP (N-MGGP)), was proposed to formulate the functional relationship between the water content and two input parameters (soil suction and volumetric crop root content). The proposed approach makes use of a statistical approach of stepwise regression and classification methods (Bayes naive and artificial neural network (ANN)) to tackle the two issues. Simulated data obtained from the models was evaluated against the experimental data. Findings - The performance of proposed approach was found to better than that of standardized MGGP. Sensitivity and parametric analysis conducted validates the robustness of model by unveiling dominant input parameters and hidden non-linear relationships. Originality/value - To the best of authors' knowledge, an empirical model is developed that measures the effect of crop root content on the SWRCs. The authors also proposed a new genetic programming approach in simulating the crop root content dependent SWRCs.
 
Publisher EMERALD GROUP PUBLISHING LIMITED
 
Date 2016-01-15T08:48:15Z
2016-01-15T08:48:15Z
2015
 
Type Article
 
Identifier ENGINEERING COMPUTATIONS, 32(3)914-930
0264-4401
1758-7077
http://dx.doi.org/10.1108/EC-05-2014-0110
http://dspace.library.iitb.ac.in/jspui/handle/100/18201
 
Language en