Regeneration assessment inuneven-aged mixed species stands using neural networks;Zur Schatzung der Verjungungssituation in Mischbestanden mit Hilfe Neuraler Netze

Forstwissenschaftliches Centralblatt

Volumn 119, Issue 6, 2000, Pages 350-366

  Hasenauer V H Kindermann, G ^a   Merkl, D ^a  

^a UNIVERSITY OF NATURAL RESOURCES AND LIFE SCIENCES   (Austria)

Author keywords

Neural networks; Regeneration; Uneven aged mixed stands

Indexed keywords

ARTIFICIAL NEURAL NETWORK; ASSESSMENT METHOD; REGENERATION; STAND STRUCTURE;

EID: 0034490584     PISSN: 00158003     EISSN: None     Source Type: Journal    
DOI: 10.1007/BF02769149     Document Type: Article

References (32)

1. Die Winkelzähiprobe
2. Die Entwicklung von Bergmischwaldkulturen in den Chiemgauer Alpen
3. Grundriß des Waidbaues
4. Light regimes beneath closed canopies and tree-tall gaps in temperate and tropical forests
5. Sunflecks and their importance to forest understory plants
6. FOREST A computer model for simulating the growth and reproduction of mixed species forest stands Univ. Wisconsin-Madison
7. Predicting regeneration establishment with the PROGNOSIS model
8. Strahlung and Wind an Bestandesrändern
9. Instruktioner für die Feldarbeit der Österreichischen Forstinventur
10. Predicting juvenile tree height growth in uneven-aged mixed species stands in Austria
11. A dynamic analysis of age in sugar maple seedings
12. Waldbau vor neuer Herausforderungen bei der Waldverjüngung und Jungbestandspflege
13. Dynamics of an uneven-aged forest stand
14. Dynamics and simulated yield of Douglas-fir
15. A stochastic spatial regeneration model for Pinus silvestris
16. Perfecting a stand-density index for even-aged forests
17. Seedling recruitment in forests: Calibrating models to predict patterns of tree seedling dispersion
18. A direct and adaptive method for faster backpropagation learning: The Rprop algorithm
19. Learning representations by back-propagating errors
20. A model describing natural regneration recruitment of Norway spruce (Picea abies L.) in Austria
21. A generalized methodology for estimating forest ingrowth at multiple treshold diameters
22. Forest succession models: A rationale and methodology for modeling forest succession over large regions
23. FIBER 3.0 An ecological growth model for northeastern forest types
24. SNNS-Stuttgart Neural Network Simulator