Further Reading

Aoki I, Komatsu T, and Hwang K (1999) Prediction of response of zooplankton biomass to climatic and oceanic changes. Ecological Modelling 120(2-3): 261-270. Allaby M (1996) Basics of Environmental Science. London: Routledge. Bell JF (1999) Tree based methods. In: Fielding AH (ed.) Machine Learning Methods for Ecological Applications, pp. 89-105. Dordrecht, The Netherlands: Kluwer Academic Publishers. Breiman L, Friedman J, Olshen R, and Stone C (1984) Classification and

Regression Trees. Belmont, CA: Wadsworth. Brosse S, Guegan J-F, Tourenq J-N, and Lek S (1999) The use of artificial neural networks to assess fish abundance and spatial occupancy in the littoral zone of a mesotrophic lake. Ecological Modelling 120(2-3): 299-311. Clark P and Boswell R (1991) Rule induction with CN2: Some recent improvements. In: Proceedings of the Fifth European Working Session on Learning, pp. 151-163. Berlin: Springer. Debeljak M, DZeroski S, Jerina K, Kobler A, and Adamic M (2000) Habitat suitability modelling of red deer (Cervus elaphus L.) in south-central Slovenia. Ecological Modelling 138: 321-330. Debeljak M, DZeroski S, and Adamic; M (1999) Interactions among the red deer (Cervus elaphus L.) population, meteorological parameters and new growth of the natural regenerated forest in SneZnik, Slovenia. Ecological Modelling 121(1): 51-61. DZeroski S (2001) Data mining in a nutshell. In: DZeroski S and Lavracc N

(eds.) Relational Data Mining, pp. 3-27. Berlin: Springer. DZeroski S (2002) (Applications of KDD in) environmental sciences. In: Kloesgen W and Zytkow JM (eds.) Handbook of Data Mining and Knowledge Discovery, pp. 817-830. Oxford: Oxford University Press.

DZeroski S and Grbovic J (1995) Knowledge discovery in a water quality database. In: Proceedings of the First International Conference on Knowledge Discovery and Data Mining, pp. 81-86. Menlo Park, CA: AAAI Press.

DZeroski S, Todorovski L, Bratko I, Kompare B, and KriZman V (1999) Equation discovery with ecological applications. In: Fielding AH (ed.) Machine Learning Methods for Ecological Applications, pp. 185-207. Boston: Kluwer Academic. Fayyad U, Piatetsky-Shapiro G, and Smyth P(1996) From data mining to knowledge discovery: An overview. In: Fayyad U, Piatetsky-Shapiro G, Smyth P, and Uthurusamy R (eds.) Advances in Knowledge Discovery and Data Mining, pp. 1-34. Cambridge, MA: MIT Press.

Fielding AH (1999) An introduction to machine learning methods. In: Fielding AH (ed.) Machine Learning Methods for Ecological Applications, pp. 1-35. Dordrecht, The Netherlands: Kluwer Academic.

Fielding AH (ed.) (1999) Machine Learning Methods for Ecological Applications. Dordrecht, The Netherlands: Kluwer Academic.

Frawley W, Piatetsky-Shapiro G, and Matheus C (1991) Knowledge discovery in databases: An overview. In: Piatetsky-Shapiro G and Frawley W (eds.) Knowledge Discovery in Databases, pp. 1-27. Cambridge, MA: MIT Press.

Han J and Kamber M (2001) Data Mining: Concepts and Techniques. San Francisco: Morgan Kaufmann.

Hogg RV and Craig AT (1995) Introduction to Mathematical Statistics, 5th edn. Englewood Cliffs, NJ: Prentice Hall.

Jeffers JNR (1999) Genetic algorithms. In: Fielding AH (ed.) Machine Learning Methods for Ecological Applications, pp. 107-121. Dordrecht, The Netherlands: Kluwer Academic.

Kampichler C, DZeroski S, and Wieland R (2000) The application of machine learning techniques to the analysis of soil ecological data bases: Relationships between habitat features and Collembola community characteristics. Soil Biology and Biochemistry 32: 197-209.

Kaufman L and Rousseeuw PJ (1990) Finding Groups in Data: An Introduction to Cluster Analysis. New York: Wiley.

Kobler A and Adamic M (1999) Brown bears in Slovenia: Identifying locations for construction of wildlife bridges across highways. In: Proceedings of the Third International Conference on Wildlife Ecology and Transportation, pp. 29-38. Tallahassee, FL: Florida Department of Transportation.

Kompare B and DZeroski S (1995) Getting more out of data: Automated modelling of algal growth with machine learning. In: Proceedings of the International Conference on Coastal Ocean Space Utilization pp. 209-220. University of Hawaii.

Kompare B, DZeroski S, and Karalicc A (1997) Identification of the Lake of Bled ecosystem with the artifical intelligence tools M5 and FORS. In: Proceedings of the Fourth International Conference on Water Pollution, pp. 789-798. Southampton: Computational Mechanics Publications.

Kompare B, DZeroski S, and KriZman V (1997) Modelling the growth of algae in the Lagoon of Venice with the artificial intelligence tool GoldHorn. In: Proceedings of the Fourth International Conference on Water Pollution, pp. 799-808. Southampton: Computational Mechanics Publications.

Lek-Ang S, Deharveng L, and Lek S (1999) Predictive models of collembolan diversity and abundance in a riparian habitat. Ecological Modelling 120(2-3): 247-260.

Lek S and Guegan JF (eds.) (1999) Special Issue: Application of Artificial Neural Networks in Ecological Modelling. Ecological Modelling , Ecological Modelling 120(2-3). 65-73.

OZesmi SL and OZesmi U (1999) An artificial neural network approach to spatial habitat modeling with interspecific interaction. Ecological Modelling 116(1): 15-31.

Quinlan JR (1986) Induction of decision trees. Machine Learning 1: 81-106.

Recknagel F, French M, Harkonen P, and Yabunaka K (1997) Artificial neural network approach for modelling and prediction of algal blooms. Ecological Modelling 96(1-3): 11-28.

Scardi M and Harding LW (1999) Developing an empirical model of phytoplankton primary production: A neural network case study. Ecological Modelling 120(2-3): 213-223.

Schleiter IM, Borchardt D, Wagner R, et al. (1999) Modelling water quality, bioindication and population dynamics in lotic ecosystems using neural networks. Ecological Modelling 120(2-3): 271-286.

Stankovski V, Debeljak M, Bratko I, and Adamic M (1998) Modelling the population dynamics of red deer (Cervus elaphus L.) with regard to forest development. Ecological Modelling 108(1-3): 145-153.

Taylor P (1999) Statistical methods. In: Berthold M and Hand DJ (eds.) Intelligent Data Analysis: An Introduction, pp. 67-127. Berlin: Springer.

Todorovski L, DZeroski S, and Kompare B (1998) Modelling and prediction of phytoplankton growth with equation discovery. Ecological Modelling 113: 71-81.

Was this article helpful?

0 0
10 Ways To Fight Off Cancer

10 Ways To Fight Off Cancer

Learning About 10 Ways Fight Off Cancer Can Have Amazing Benefits For Your Life The Best Tips On How To Keep This Killer At Bay Discovering that you or a loved one has cancer can be utterly terrifying. All the same, once you comprehend the causes of cancer and learn how to reverse those causes, you or your loved one may have more than a fighting chance of beating out cancer.

Get My Free Ebook


Post a comment