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How does statistical error of yarding models affect optimal road network?
Conference paper

How does statistical error of yarding models affect optimal road network?

Mohammad R Ghaffariyan, K Stampfer, J Sessions and M J Lexer
Proceedings of the 42nd International Symposium on Forestry Mechanisation, pp.146-152
International Symposium on Forestry Mechanisation, 42nd (Kostelec, Czech Republic, 21-Jun-2009–24-Jun-2009)
FORMEC
2009
url
http://www.formec.org/images/proceedings/2009/formec_2009.pdfView
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Abstract

Forestry Sciences Transportation and Freight Services Confidence interval Yarding Optimal road spacing Multiple criteria decision making
In forest engineering, time prediction models are common tools for evaluating production study of different forest machineries depending on stand and terrain parameters. Usually these models are developed using multiple regression method based on the statistical data collected by different time study methods. Regarding to multiple regression, there are two assumptions; (1) the depended variables are nonstochastic and (2) the x's are measured without error. The assumptions cannot be validated, so they do not play a major in the analysis. However, they do influence interpretation of the regression results. In this paper, firstly the confidence interval curves of the parameters used in the yarding and installation time prediction models of tower yarder in Austria are presented. The second part of this study deals with the effect of the error of these multiple regression models on optimal road spacing of tower yarder based on the minimization of total costs of roading, yarding and installation. Finally to choose the best optimal spacing under uncertainty, we implemented the multiple criteria decision making process and PROMETHEE considering the criteria like minimum total cost (Euro/m3 ) as economical criteria, soil erosion, soil compaction in the skid trail, area of constructed roads (m2 /ha), reforestation costs and facilitating the silvicutural treatments to the stands. The optimal road spacing of 164 m was selected as best solution under uncertainty caused by error.

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