Article ID: | iaor20011396 |
Country: | Canada |
Volume: | 38 |
Issue: | 3 |
Start Page Number: | 145 |
End Page Number: | 160 |
Publication Date: | Aug 2000 |
Journal: | INFOR |
Authors: | Michalowski Wojtek, Slowinski Roman, Nilsson Sten, Flinkman Matti, Susmaga Robert, Wilk Szymon |
Keywords: | decision: rules, artificial intelligence: decision support |
This paper attempts to identify attributes that are considered essential for a development of sustainable forest management practices in the Siberian forests. This goal is accomplished through an analysis of net primary production of phytomass (NPP), which is used to classify the Siberian ecoregions into compact and cohesive NPP performance classes. Rough Sets analysis is used as a data mining methodology for the evaluation of the Siberian forest database. In order to interpret relationships between various forest characteristics, relationships known as interesting rules are generated on a basis of a reduced problem description.