Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests

Ecological Modelling

Volumn 221, Issue 8, 2010, Pages 1119-1130

  Aertsen, Wim ^a   Kint, Vincent ^a   van Orshoven, Jos ^a   Özkan, Kürşad ^b   Muys, Bart ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b SULEYMAN DEMIREL UNIVERSITY   (Turkey)

Author keywords

Artificial neural networks; Boosted regression trees; Forest site classification; Generalized additive models; Multi criteria decision analysis; Multiple linear regression; Predictive modelling

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BOOSTED REGRESSION TREES; FOREST SITE CLASSIFICATION; GENERALIZED ADDITIVE MODEL; MULTI-CRITERIA DECISION ANALYSIS; MULTIPLE LINEAR REGRESSIONS; PREDICTIVE MODELLING;

DECISION MAKING; DECISION THEORY; ECOLOGY; LANDFORMS; LEARNING SYSTEMS; LINEAR REGRESSION; NEURAL NETWORKS; SOILS; VEGETATION;

FORESTRY;

CLIMATE PREDICTION; CONIFEROUS TREE; ECOSYSTEM MODELING; INDEX METHOD; MONTANE FOREST; PARAMETERIZATION; PHYSICAL GEOGRAPHY; REGRESSION ANALYSIS; SITE INVESTIGATION; STAND DYNAMICS; TOPOGRAPHIC EFFECT; VULNERABILITY;

DECISION MAKING; ECOLOGY; FORESTRY; FORESTS; MATHEMATICAL MODELS; NEURAL NETWORKS; REGRESSION ANALYSIS; SOIL;

TAURIDES; TURKEY;

CEDRUS; CEDRUS LIBANI; PINUS BRUTIA; PINUS NIGRA;

EID: 77349088324     PISSN: 03043800     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecolmodel.2010.01.007     Document Type: Article

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