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Stefan Daume (email), Dave Robertson

A heuristic approach to modelling thinnings

Daume S., Robertson D. (2000). A heuristic approach to modelling thinnings. Silva Fennica vol. 34 no. 3 article id 628. https://doi.org/10.14214/sf.628

Abstract

Thinnings play an important role in guiding forest development and are considered by many to be the most important influence on forests in Central Europe. Due to their importance, thinning models are a major part of any forest growth model for managed forests. Existing thinning model approaches have a number of problems associated with structure and model development that weaken their reliability and accuracy. To overcome some of these problems this paper proposes a heuristic approach to modelling thinnings, where the focus is on distance-dependent, single-tree models. This alternative approach tries to capture the information, strategies and deductive processes likely to be employed by a forester deciding on the removal of individual trees in a stand. Use of heuristics to represent thinning knowledge simplifies the construction and refinement of a thinning model and increases its plausibility. The representation of thinning heuristics in Prolog – a programming language based on formal logic – is a straightforward process without losing expressiveness of the original heuristics. Limited tests of the model implemented in Prolog indicate that the proposed model outperforms its competitors.

Keywords
thinning; heuristic model; rule-based; knowledge-based

Author Info
  • Daume, The University of Edinburgh, Institute for Representation and Reasoning, Division of Informatics, 80 South Bridge, Edinburgh EH1 1HN, United Kingdom E-mail stefand@dai.ed.ac.uk (email)
  • Robertson, The University of Edinburgh, Institute for Representation and Reasoning, Division of Informatics, 80 South Bridge, Edinburgh EH1 1HN, United Kingdom E-mail dr@nn.uk

Received 21 June 1999 Accepted 15 June 2000 Published 31 December 2000

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Available at https://doi.org/10.14214/sf.628 | Download PDF

Creative Commons License CC BY-SA 4.0

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