• Journal of Korean Society of Forest Science
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• v.84 no.1
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• pp.63-70
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• 1995

This paper discusses applications of neural network to stand stocking control problems. The scope of this research was to develop a neural network model for finding optimal stand management regimes and examining the performance of the model for field application. Performance was analyzed in consideration of the number of training examples and structural aspects of neural network. Research on network performance was based on extensive optimization studies for pure longleaf pine(Pinus palustris) stands. For experimental purposes. an existing nonlinear even-aged stand optimization model with a whole-stand growth and yield simulator was used to generate data samples required for the performance analysis.

• Journal of Korean Society of Forest Science
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• v.104 no.4
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• pp.649-656
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• 2015

The objective of this study was to analyze the optimal thinning regimes for timber or carbon managements in Cryptomeria japonica stands of Hannam Experimental Forest, Korea Forest Research Institute. In solving the problem, PATH algorithm, developed by Paderes and Brodie, was used as the decision-making tool and the individual-tree/distance-free stand growth simulator for the species, developed by Kwon et al., was used to predict the stand growth associated with density control by thinning regimes and mortality. The results of this study indicate that the timber management for maximum net present value (NPV) needs less number of but higher intensity thinnings than the carbon management for maximum carbon absorption does. In case of carbon management, the amount of carbon absorption is bigger than that of timber management by about 6% but NPV is reduced by about 3.2%. On the other hand, intensive forest managements with thinning regimes promotes net income and carbon absorption by about 60% compared with those of the do-nothing option.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.06b
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• pp.305-309
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• 2006

This paper presents and illustrates the application of a growth and yield model that supports both forest and mill side volume and value estimates. Traditional forest stand growth and yield models represent the forest landowner view of yield and economics. Predicted yields are estimates of what one would expect from a procurement cruise, and current stumpage prices are applied to investigate optimum management strategies. Optimum management regimes and rotation ages obtained from the forest side view are unlikely to be economically optimal when viewed from the mill side. The actual distribution of recoverable manufactured product and its value are highly dependent on mill technologies and configurations. Overcoming this limitation of growth and yield computer models necessitates the ability to predict and price the expected manufactured distribution of lumber, lineal meters of veneer, and tonnes of air dried pulp fiber yield. With these embedded models, users of the yield simulator can evaluate the economics of possible/feasible management regimes from both the forest and mill business sides. The simulator is a forest side model that has been modified to produce estimates of manufactured product yields by embedding models for 1) pulpwood chip size class distribution and pulp yield for any kappa number (Schultz and Matney, 2002), 2) a lumber yield and pricing model based on the Best Opening Face model developed by the USDA Forest Service Forest Products Laboratory (Lewis, 1985a and Lewis, 1985b), and 3) a lineal meter veneer model derived from peeler block tests. While the model is strictly applicable to planted loblolly pine (Pinus taeda L.) on cutover site-prepared land in the United States (US) Gulf South, the model and computer program are adaptable to any region and forest type.