NONINDUSTRIAL PRIVATE FOREST LANDOWNER'S CHOICE OF TIMBER MANAGEMENT STRATEGY: PREDICTING THE CUTTING LEVEL WITH GENETIC ALGORITHM

摘要

In the study, a set of rules is generated to predict the nonindustrial private forest (NIPF) landowners' choices of the preferred management strategies with the variables describing the characteristics of the landowners an their forest holdings. The rules are induced from the database by applying a genetic-based learning algorithms. The fitness of the rules is tested with the general linear regression analysis using the same data.