Prediction of tree stems to improve efficiency in automatized harvesting of forests
针对森林采伐中树干测量不完整的问题，基于混合模型开发了一种预测方法，用于预测树干未知部分，从而优化切割决策。
The problem of predicting future observations on a statistical unit given past measurements on the same and other similar units is frequently encountered in practical applications. When computer-based marking for bucking routines is used in a forest processor, it is usually not feasible to run the whole tree stem through the measuring device before the first cutting decisions have to be made. However, for optimal conversion of single stems into smaller logs, the whole stem should be measured in advance. To this end we have developed a predictor for the unknown part of the stem under the mixed model for repeated measurements. Our prediction-based approach provides an eminently satisfactory solution to this important marking for bucking problem under incomplete information.