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Applying Fuzzy Logic to Tree Bucking Control

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In this article, we introduce a fuzzy logic based control system that calibrates the price list controlling the tree bucking of a modern harvester according to the unique conditions of an individual stand prior to harvesting. The system employs a bucking simulator that predicts an output distribution for any price list generated. A fuzzy controller is used to recalculate the price list according to the difference between the demand distribution and the actual output distribution. The tests with perfect knowledge of the stems showed that the control system clearly works efficiently. However, calibrating the price list prior to harvesting seemed to be very sensitive to the precision of the prior information on the trees. The simulations showed that while no gain can be achieved by preharvest inventorying of the stands and fine-tuning the price lists with this imperfect knowledge, the same or even better bucking results can be obtained by the bucking-to-demand process in which the price list is continuously adjusted after each cutting. For. Sci. 48(4):673–684.

Keywords: Optimal bucking; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; fuzzy control; harvesting; natural resource management; natural resources

Document Type: Miscellaneous

Affiliations: 1: Research Scientist Department of Forest Resource Management, University of Helsinki, P.O. Box 27 00014 Finland, Phone:+358-9-19158194; Fax:+358-9-19158159 2: Professor of Forest Engineering Faculty of Forestry, University of Joensuu, P.O. Box 111 80101 Joensuu, Finland,

Publication date: 2002-11-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2015 Impact Factor: 1.702
    Ranking: 16 of 66 in forestry

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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