174
T.-S. Chon . Y.S. Park' I.-S. Kwak: . E.Y. Cha
grouped by the Kohonen network and community-exergy relationships were
effectively pattemed by the multi-Iayer perceptron with the backpropagation
algorithm.
Acknowledgements
The analysis in this research was in part supported by "KOSEF ROOl-200100087".
References
Allan JD (1995) Stream Ecology 'Structure and function of running waters'. Chapman &
hall, 388 pp
Allen TFH, Starr TB (1982) Hierarchy. The University of Chicago Press, 310 pp
Boudjema G, Chau NP (1996) Revealing dynamies of ecological systems from natural
recordings. Ecol. Model., 91, 15-23
Bunn SE, Edward DH, Loneragan NR (1986) Spatial and temporal variation in the
macroinvertebrate fauna of streams of the northern jarrah forest, Western Australia:
community structure. Freshwater Biology, 16,67-91
Brosse S, Lek S, Townsend CR (2001) Abundance, diversity, and structure of freshwater
invertebrates and fish communities: an artificial neural network approach. New
Zealand Journal of Marine and Freshwater Research, 35, l35-145
Calow P, Petts GE (1994) The Rivers Handbook ' hydrological and ecological principles'.
Blackwell Scientific Publications, 523 pp
Carpenter GA, Grossberg S (1987) ART2: self-organization of stable category recognition
codes for analog input patterns. Applied Optics, 26, 4919-4930
Chon TS, Park YS, Moon KH, Cha EY (1996) Patternizing communities by using an
artificial neural network. Ecol. Model., 90, 69-78
Chon TS, Kwak IS, Park YS (2000a) Pattern recognition of long-term ecological data in
community changes by using artificial neural networks: Benthic macroinvertebrates
and chironornids in apolluted stream. Korean J. Ecol., 23, 89-100
Chon TS, Park YS, Cha EY (2000b) Patterning of community changes in benthic
macroinvertebrates collected from urbanized streams for the short time prediction by
temporal artificial neural networks. In: Lek, S. and Guegan, lF. (Eds.), Artificial
Neuronal Networks: Application to Ecology and Evolution. Springer-Verlag, Berlin,
pp. 99-114
Chon TS, Park YS, Park JH (2000c) Deterrnining temporal pattern of community dynamies
by using unsupervised leaming algorithms. Ecol. Model., l32, 151-166
Chon TS, Kwak IS, Park YS, Kim TH, Kim YS (2001) Patterning and short-term
predictions of benthic macroinvertebrate community dynamies by using a recurrent
artificial neural network. Ecol. Model., 146. (In Press)
Cumrnins KW (1974) Structure and function of stream ecosystems. Bioscience, 24, 631641
T.-S. Chon . Y.S. Park' I.-S. Kwak: . E.Y. Cha
grouped by the Kohonen network and community-exergy relationships were
effectively pattemed by the multi-Iayer perceptron with the backpropagation
algorithm.
Acknowledgements
The analysis in this research was in part supported by "KOSEF ROOl-200100087".
References
Allan JD (1995) Stream Ecology 'Structure and function of running waters'. Chapman &
hall, 388 pp
Allen TFH, Starr TB (1982) Hierarchy. The University of Chicago Press, 310 pp
Boudjema G, Chau NP (1996) Revealing dynamies of ecological systems from natural
recordings. Ecol. Model., 91, 15-23
Bunn SE, Edward DH, Loneragan NR (1986) Spatial and temporal variation in the
macroinvertebrate fauna of streams of the northern jarrah forest, Western Australia:
community structure. Freshwater Biology, 16,67-91
Brosse S, Lek S, Townsend CR (2001) Abundance, diversity, and structure of freshwater
invertebrates and fish communities: an artificial neural network approach. New
Zealand Journal of Marine and Freshwater Research, 35, l35-145
Calow P, Petts GE (1994) The Rivers Handbook ' hydrological and ecological principles'.
Blackwell Scientific Publications, 523 pp
Carpenter GA, Grossberg S (1987) ART2: self-organization of stable category recognition
codes for analog input patterns. Applied Optics, 26, 4919-4930
Chon TS, Park YS, Moon KH, Cha EY (1996) Patternizing communities by using an
artificial neural network. Ecol. Model., 90, 69-78
Chon TS, Kwak IS, Park YS (2000a) Pattern recognition of long-term ecological data in
community changes by using artificial neural networks: Benthic macroinvertebrates
and chironornids in apolluted stream. Korean J. Ecol., 23, 89-100
Chon TS, Park YS, Cha EY (2000b) Patterning of community changes in benthic
macroinvertebrates collected from urbanized streams for the short time prediction by
temporal artificial neural networks. In: Lek, S. and Guegan, lF. (Eds.), Artificial
Neuronal Networks: Application to Ecology and Evolution. Springer-Verlag, Berlin,
pp. 99-114
Chon TS, Park YS, Park JH (2000c) Deterrnining temporal pattern of community dynamies
by using unsupervised leaming algorithms. Ecol. Model., l32, 151-166
Chon TS, Kwak IS, Park YS, Kim TH, Kim YS (2001) Patterning and short-term
predictions of benthic macroinvertebrate community dynamies by using a recurrent
artificial neural network. Ecol. Model., 146. (In Press)
Cumrnins KW (1974) Structure and function of stream ecosystems. Bioscience, 24, 631641