The analysis of artificial neural network data models

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1280, Issue , 1997, Pages 337-346

  Roadknight, C M ^a   Palmer Brown, D ^a   Mills, G E ^a  

^a NOTTINGHAM TRENT UNIVERSITY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

COMPLEX NETWORKS; COMPUTATIONAL COMPLEXITY; DATA HANDLING; FUNCTIONS; INFORMATION ANALYSIS;

CORRELATED ACTIVITY; HIDDEN UNITS; MODELLING ENVIRONMENT; NONLINEAR FUNCTIONS; POLLUTANT IMPACT; RELATIVE WEIGHTS; SCIENTIFIC DATA; SIMPLIFIED EQUATIONS;

MULTILAYER NEURAL NETWORKS;

EID: 84949801873     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/bfb0052852     Document Type: Conference Paper

References (21)

1. Benton J, Fuhrer J, Gimeno BS, Skarby L, Balls G, Palmer-Brown D, Roadknight C and Sanders G.1996. ICP-Crops and critical levels of ozone for injury development. Exceedences of Critical Loads and Levels. In Exceedences of Critical Loads and Levels. Eds. M. Knoflacher, J. Schneider and G. Soja. Umweltbundesamt (Federal Environment Agency) Wein, Austria. 97-112.
2. Benton J, Fuhrer J, Gimeno BS, Skarby L, Balls G, Roadknight C and Sanders-Mills G. 1996. The critical level of ozone for visible injury on crops and natural vegetation (ICP-Crops). In: Critical Levels of Ozone in Europe: Testing and Finalising the Concepts. UN ECE Workshop Report. Eds. L Karenlampi and L Skarby. University of Kuopio, Finland. 44-57.
3. Heck, WW, Taylor O. and Tingley DT. (eds) 1988. Assessment of Crop Loss from Air Pollutants. Elsevier Applied Science, New York.
4. Funahashi K. 1989. On the approximate realization of continuous mappings by neural networks. Neural Networks, 2, 183-192.
5. Burke HB, Hoang A and Rosen DB. 1995. Survival function estimates in cancer using artificial neural networks. Proceedings of WCNN. Vol II. p.748-749.
6. Orr RK. 1995. Use of probabilistic neural networks to predict mortality following cardiac surgery. Proceedings of WCNN. Vol II. p. 754-757.
7. Davalo E, Niam P. 1990. Neural Networks. Macmillan Press, p. 111-112.
8. Tan H, Prokhorov DV and Wunsch DC. 1995. Probabilistic and time-delay neural network techniques for conservative short-term stock trend prediction. Proceedings of World Congress on Neural Networks. Vol II. p. 44-47.
9. Fu L. 1994. Neural Networks in Computer Intelligence. McGraw-Hill International Editions, p.351-369.
10. Andrews R, Diederich J and Tickle AB. 1995. A survey and critique of techniques for extracting rules from trained Artificial Neural Networks. Knowledge Based Systems Vol 8 (6, December) p. 373-389.
11. Sestito S and Dillon T. 1994. Automatic knowledge acquisition. Prentice Hall.
12. Towell G and Shavlik J. 1993. The extraction of refined rules from knowledge based neural networks. Machine Learning Vol 131, p71-101.
13. Karin ED. 1990. A simple procedure for pruning back-propagation trained neural networks. I.E. Trans. Neural Networks, vol.1 no.2. p239-242.
14. Weigend AS, Rumelhart DE and Huberman BA. 1991. Generalization by weight elimination with applications to forecasting. In Advances in Neural Information Processing (3). Lippmann R, Moody J and Touretzky D. Eds. p. 875-882.
15. Balls GR, Palmer-Brown D, Cobb AH and Sanders GE. 1995. Towards unravelling the complex interactions between microclimate, ozone dose and ozone injury in clover. Journal of Water, Air and Soil Pollution. 85, 1467-1472.
16. Balls GR, Palmer-Brown D, and Sanders GE. 1996. Investigating microclimate influences on ozone injury in clover (Trifolium subterraneum) using artificial neural networks. New Phytologist, 132, 271-280
17. Roadknight CM, Palmer-Brown D and Sanders GE. 1995. Learning the equations of data. Proceedings of 3rd annual SNN symposium on neural networks (eds. Kappen B and Gielen S) Springer-Verlag. 253-257.
18. Roadknight CM, Balls GR, Sanders GE and Palmer-Brown D. Modelling complex environmental data. IEEE Transactions on Neural Networks: Special edition on everyday applications. (In Press July 1997.)
19. Sietsma J and Dow RJF. 1988. Neural net pruning-Why and how. Pre. IEEE Int. Conf. Neural Networks. Vol 1. p. 325-333.
20. Wiersma FR, Poel M and Oudshoff AM. 1995. The BB neural network rule extraction method. Proceedings of 3rd annual SNN symposium on neural networks (eds. Kappen B and Gielen S) Springer-Verlag. 69-73.
21. Ripley BD. 1995. Statistical ideas for selecting network architectures. Proceedings of 3rd annual SNN symposium on neural networks (eds. Kappen B and Gielen S) Springer-Verlag. 183-190.