A software tool for the estimation of wood harvesting productivity using the kNN method
For operational planning and management of wood harvests it is important to have access to reliable information on time consumption and costs. To estimate these efficiently and reliably, appropriate methods and calculation tools are needed. The present article investigates whether use of the method of the k nearest neighbours (kNN) is appropriate in this case. The kNN algorithm is first explained, then is applied to two sets of data “combined cable crane and processor” and “skidder”, both containing wood harvesting figures, and thus the estimation accuracy of the method is determined. It is shown that the kNN method's estimation accuracy lies within the same order of magnitude as that of a multiple linear regression. Advantages of the kNN method are that it is easy to understand and to visualize, together with the fact that estimation models do not become out of date, since new data sets can be constantly taken into account. The kNN Workbook has been developed by the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL). It is a software tool with which any data set can be analysed in practice using the kNN method. This tool is also presented in the article.
Safe Tumbling of Heavy Objects Using a Two-Cable Crane
