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Volumn 32, Issue 9, 2012, Pages 2393-2398
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Using different data mining algorithms to predict soil organic matter based on visible-near infrared spectroscopy
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Author keywords
Modeling; Paddy soil; Soil organic matter; Vis NIR spectroscopy
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Indexed keywords
BLACK BOXES;
CALIBRATION AND VALIDATIONS;
COMBINED METHOD;
DATA MINING ALGORITHM;
DATA SETS;
INTERPRETABILITY;
NON-LINEAR MODEL;
PADDY SOILS;
PREDICTION ACCURACY;
PREDICTIVE ABILITIES;
RANDOM FORESTS;
SOIL ORGANIC MATTERS;
SOIL PROPERTY;
SOIL SENSING;
SUPPORTED VECTOR MACHINES;
VIS-NIR SPECTROSCOPY;
VISIBLE-NEAR INFRARED SPECTROSCOPY;
ZHEJIANG PROVINCE;
ALGORITHMS;
BIOGEOCHEMISTRY;
BIOLOGICAL MATERIALS;
DATA MINING;
DECISION TREES;
FORECASTING;
INFRARED DEVICES;
INFRARED SPECTROSCOPY;
MODELS;
NEAR INFRARED SPECTROSCOPY;
NEURAL NETWORKS;
NONLINEAR SYSTEMS;
ORGANIC COMPOUNDS;
SOILS;
GEOLOGIC MODELS;
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EID: 84867165243
PISSN: 10000593
EISSN: None
Source Type: Journal
DOI: 10.3964/j.issn.1000-0593(2012)09-2393-06 Document Type: Article |
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Times cited : (47)
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References (11)
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