-
1
-
-
2342565172
-
The effects of adding noise during backpropagation training on a generalization performance
-
An, G., 1996, The effects of adding noise during backpropagation training on a generalization performance: Neural Computation, v. 8, no. 3, p. 643-647.
-
(1996)
Neural Computation
, vol.8
, Issue.3
, pp. 643-647
-
-
An, G.1
-
3
-
-
33646847347
-
Artificial neural networks: A new method of mineral prospectivity mapping
-
Univ.Western Australia (Perth)
-
Brown, W. M., 2002, Artificial neural networks: a new method of mineral prospectivity mapping: unpubl. doctoral dissertation, Univ.Western Australia (Perth), 760 p.
-
(2002)
Unpubl. Doctoral Dissertation
, pp. 760
-
-
Brown, W.M.1
-
4
-
-
33947234500
-
Use of fuzzy membership input layers to combine subjective geological knowledge and empirical data in a neural network method for mineral potential mapping
-
press
-
Brown, W. M., Groves, D. I., and Gedeon, T. D., 2002, Use of fuzzy membership input layers to combine subjective geological knowledge and empirical data in a neural network method for mineral potential mapping: Natural Resources Research, v. 12, no. 3, in press.
-
(2002)
Natural Resources Research
, vol.12
, Issue.3
-
-
Brown, W.M.1
Groves, D.I.2
Gedeon, T.D.3
-
5
-
-
78649621028
-
Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping
-
Bayer,U., and Burger, H., and Skala,W., eds.
-
Brown, W. M., Baddeley, A., Gedeon, T. D., and Groves, D. I., 2002, Bivariate J-function and other graphical statistical methods help select the best predictor variables as inputs for a neural network method of mineral prospectivity mapping, in Bayer,U., and Burger, H., and Skala,W., eds.,IAMG2002: 8th Ann. Conf. Intern. Assoc. Mathematical Geology (Berlin), v. 1, p. 263-268.
-
(2002)
IAMG2002: 8th Ann. Conf. Intern. Assoc. Mathematical Geology (Berlin)
, vol.1
, pp. 263-268
-
-
Brown, W.M.1
Baddeley, A.2
Gedeon, T.D.3
Groves, D.I.4
-
6
-
-
0033816133
-
Artificial neural networks: A new method for mineral prospectivity mapping
-
Brown, W. M., Gedeon, T. D., Groves, D. I., and Barnes, R. G., 2000, Artificial neural networks: a new method for mineral prospectivity mapping: Australian Jour. Earth Sciences, v. 47, no. 4, p. 757-770.
-
(2000)
Australian Jour. Earth Sciences
, vol.47
, Issue.4
, pp. 757-770
-
-
Brown, W.M.1
Gedeon, T.D.2
Groves, D.I.3
Barnes, R.G.4
-
7
-
-
78649604266
-
Application of artifical neural networks to prospectivity analysis in a GIS environment: A comparison with statistical and fuzzy logic methods for Au and Sn deposits of the Tenterfield area, NSW (abst.)
-
Brown, W. M., Taylor, G. R. T., Jusmady, Groves, D. I., and Knox- Robinson,C. M., 1997, Application of artifical neural networks to prospectivity analysis in a GIS environment: a comparison with statistical and fuzzy logic methods for Au and Sn deposits of the Tenterfield area, NSW (abst.), in 14th Australian Geol. Conv. Abstracts, Geol. Soc. Australia, v. 49, p. 57.
-
(1997)
14th Australian Geol. Conv. Abstracts, Geol. Soc. Australia
, vol.49
, pp. 57
-
-
Brown, W.M.1
Taylor, G.R.T.2
Jusmady Groves, D.I.3
Knox-Robinson, C.M.4
-
8
-
-
0011213245
-
Fault tolerance training improves generalization and robustness
-
New York
-
Clay, R. D., and Sequin, C. H., 1992, Fault tolerance training improves generalization and robustness, in Intern. Joint Conf. Neural Network (IJCNN 1992), IEEE, New York, v. 4, p. 769- 774.
-
(1992)
Intern. Joint Conf. Neural Network (IJCNN 1992) IEEE
, vol.4
, pp. 769-774
-
-
Clay, R.D.1
Sequin, C.H.2
-
10
-
-
0033810884
-
Late-kinematic timing of orogenic gold deposits and significance for computerbased exploration techniques with emphasis on the Yilgarn Block
-
Groves,D. I., Goldfarb,R. J., Knox-Robinson,C., Ojala, J., Gardoll, S., Yun, G., and Holyland, P., 2000, Late-kinematic timing of orogenic gold deposits and significance for computerbased exploration techniques with emphasis on the Yilgarn Block, Western Australia: Ore Geology Reviews, v. 17, no. 1, p. 1-38.
-
(2000)
Western Australia: Ore Geology Reviews
, vol.17
, Issue.1
, pp. 1-38
-
-
Groves, D.I.1
Goldfarb, R.J.2
Knox-Robinson, C.3
Ojala, J.4
Gardoll, S.5
Yun, G.6
Holyland, P.7
-
11
-
-
0346441859
-
-
Groves, D. I., Ojala, J., and Holyland, P., 1997, Use of geometric parameters of greenstone belts in conceptual exploration for orogenic lode-gold deposits: AGSO Record 1997/41, p. 103- 108.
-
(1997)
Use of Geometric Parameters of Greenstone Belts in Conceptual Exploration for Orogenic Lode-gold Deposits: AGSO Record 1997/41
, pp. 103-108
-
-
Groves, D.I.1
Ojala, J.2
Holyland, P.3
-
12
-
-
0028543366
-
Training feedforward networks with the Marquardt algorithm
-
Hagan,M.T., and Menhaj, M., 1994,Training feedforward networks with the Marquardt algorithm: IEEE Trans. Neural Networks, v. 5, no. 6, p. 989-993.
-
(1994)
IEEE Trans. Neural Networks
, vol.5
, Issue.6
, pp. 989-993
-
-
Hagan, M.T.1
Menhaj, M.2
-
13
-
-
0001858551
-
Mineral favorability mapping: A comparison of artificial neural networks logistic regression, and discriminant analysis
-
Harris, D., and Pan, G., 1999, Mineral favorability mapping: a comparison of artificial neural networks, logistic regression, and discriminant analysis: Natural Resources Research, v. 8, no. 2, p. 93-109.
-
(1999)
Natural Resources Research
, vol.8
, Issue.2
, pp. 93-109
-
-
Harris, D.1
Pan, G.2
-
14
-
-
0026624071
-
Using additive noise in back-propagation training
-
Holmstrom, L., and Koistinen, P., 1992, Using additive noise in back-propagation training: IEEE Trans. Neural Networks, v. 3, no. 1, p. 24-38.
-
(1992)
IEEE Trans. Neural Networks
, vol.3
, Issue.1
, pp. 24-38
-
-
Holmstrom, L.1
Koistinen, P.2
-
15
-
-
0000821295
-
Generalization in a linear perceptron in the presence of noise
-
Krogh, A., and Hertz, J. A., 1992, Generalization in a linear perceptron in the presence of noise: Jour. Physics A (Mathematical & General). v. 25, no. 5, p. 1135-47.
-
(1992)
Jour. Physics A (Mathematical & General)
, vol.25
, Issue.5
, pp. 1135-47
-
-
Krogh, A.1
Hertz, J.A.2
-
16
-
-
0003486924
-
-
Academic Press Inc., San Diego, California
-
Masters, T., 1993, Practical neural network recipes in C++: Academic Press Inc., San Diego, California, 493 p.
-
(1993)
Practical Neural Network Recipes in C++
, pp. 493
-
-
Masters, T.1
-
17
-
-
0026858102
-
Noise injection into inputs in back-propagation learning
-
Matsuoka, K., 1992, Noise injection into inputs in back-propagation learning: IEEE Trans. Systems, Man and Cybernetics, v. 22, no. 3, p. 436-440.
-
(1992)
IEEE Trans. Systems Man and Cybernetics
, vol.22
, Issue.3
, pp. 436-440
-
-
Matsuoka, K.1
-
18
-
-
0033339950
-
Improving the performance of multi-layer perceptrons where limited training data are available for some classes
-
Parikh, C. R., Pont, M. J., and Jones, N. B., 1999, Improving the performance of multi-layer perceptrons where limited training data are available for some classes, in ICANN99, Ninth Intern. Conf. Artificial Neural Networks, Conf. Publ. No. 470, v. 1, p. 227-232.
-
(1999)
ICANN99, Ninth Intern. Conf. Artificial Neural Networks, Conf. Publ.
, vol.1
, Issue.470
, pp. 227-232
-
-
Parikh, C.R.1
Pont, M.J.2
Jones, N.B.3
-
19
-
-
84942839657
-
An equivalence between sigmoidal gain scaling and training with noisy (jittered) input data
-
New York
-
Reed, R., Marks II, R. J., and Oh, S., 1992, An equivalence between sigmoidal gain scaling and training with noisy (jittered) input data, in RNNS/IEEE Symp. Neuroinformatics and Neurocomputers: IEEE, New York, v. 1, p. 120-127.
-
(1992)
RNNS/ IEEE Symp. Neuroinformatics and Neurocomputers: IEEE
, vol.1
, pp. 120-127
-
-
Reed, R.1
Marks II, R.J.2
Oh, S.3
-
20
-
-
0029306953
-
Similarities of error regularization, sigmoid gain scaling, target smoothing, and training with jitter
-
Reed, R., Marks II, R. J., and Oh, S., 1995, Similarities of error regularization, sigmoid gain scaling, target smoothing, and training with jitter: IEEE Trans. Neural Networks, v. 6, no. 3, p. 529- 538.
-
(1995)
IEEE Trans. Neural Networks
, vol.6
, Issue.3
, pp. 529-538
-
-
Reed, R.1
Marks II, R.J.2
Oh, S.3
-
21
-
-
0000646059
-
Learning internal representations by error Propagation
-
Rumelhart, D. E., and McClelland, J. L., eds., Cambridge, Massachusetts
-
Rumelhart, D. E., Hinton, G. E., and Williams, R. J., 1986, Learning internal representations by error Propagation, in Rumelhart, D. E., and McClelland, J. L., eds., Parallel Data Processing, M.I.T. Press, v. 1, Cambridge, Massachusetts, p. 318- 362.
-
(1986)
Parallel Data Processing, M.I.T. Press 1
, pp. 318-362
-
-
Rumelhart, D.E.1
Hinton, G.E.2
Williams, R.J.3
-
22
-
-
0026017007
-
Creating artificial neural networks that generalize
-
Sietsma, J., and Dow, R. J. F., 1991, Creating artificial neural networks that generalize: Neural Networks, v. 4, no. 1, p. 67-79.
-
(1991)
Neural Networks
, vol.4
, Issue.1
, pp. 67-79
-
-
Sietsma, J.1
Dow, R.J.F.2
-
23
-
-
0025551383
-
Improved evoked potential estimation using neural networks
-
Uncini, A., Marchesi, M., Orlandi, G., and Piazza, F., 1990, Improved evoked potential estimation using neural networks: IEEE Conf. Neural Networks (San Diego), p. II, 143-148.
-
(1990)
IEEE Conf. Neural Networks (San Diego) II
, pp. 143-148
-
-
Uncini, A.1
Marchesi, M.2
Orlandi, G.3
Piazza, F.4
-
24
-
-
0033333990
-
Training neural networks with additive noise in the desired signal
-
Wang, C., and Principe, J. C., 1999, Training neural networks with additive noise in the desired signal: IEEE Trans. Neural Networks, v. 10, no. 6, p. 1511-1517.
-
(1999)
IEEE Trans. Neural Networks
, vol.10
, Issue.6
, pp. 1511-1517
-
-
Wang, C.1
Principe, J.C.2
-
25
-
-
0001771693
-
Using GIS for mineral potential evaluation in areas with few known mineral occurrences, in Second National Forum on GIS
-
Wyborn, L. A. I., Gallagher, R., and Raymond, O., 1995, Using GIS for mineral potential evaluation in areas with few known mineral occurrences, in Second National Forum on GIS in the Geosciences-Forum Proc.: Australian Geol. Survey Organisation Record 1995/46, p. 199-211.
-
(1995)
The Geosciences-Forum Proc.: Australian Geol. Survey Organisation Record 1995/46
, pp. 199-211
-
-
Wyborn, L.A.I.1
Gallagher, R.2
Raymond, O.3
-
26
-
-
17044379546
-
Neural networks for intelligent signal processing
-
Singapore
-
Zaknich, A., 2003, Neural networks for intelligent signal processing: World Scientific, Singapore, 508 p.
-
(2003)
World Scientific
, pp. 508
-
-
Zaknich, A.1
|