[Text] : научное издание / M. Pesonen, A. Kettunen, P. Rasanen. - Helsinki : The Finnish Society of Forest Science-The Finnish Forest Resaerch Institute, 1995. - 28 p. : рис., табл. - (Acta Forestalia Fennica, ISSN 0039-3150 ; № 250). - eng. - Библиогр.: с. 26-27. -
ISBN 951-40-1491-X : 1500.00 р.
Аннотация: The aim of this study is to predict non-industrial, private forest landowners' potential
cut using a genetic algorithm and linear regression. Furthermore, the factors affecting the landownwers' strategic dicision in NIPF management planning are studied. A genetic algorithm is used to induce a set of production rules predicting NIPF landowners' preferred timber management strategies. The rules are based on the landowners' objectives and characteristics of the landowners and their forest holdings. The dependent variable is preferred timber management strategy, potential
cut, described as average annual removals of the first five-year planning period (m3/ha/a)/ The performance of genetic-based machine learning is compared to more traditional statistical analysis. The theoretical framework of study is presented in Fig. 1.
Доп.точки доступа: Kettunen, A.; Rasanen, P.
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