-
1
-
-
0029343495
-
Global optimization methods for engineering applications: A review
-
J. Arora, O. Elwakeil and A. Chahande, "Global optimization methods for engineering applications: a review", Structural Optimization, vol. 9, pp. 137-159, 1995.
-
(1995)
Structural Optimization
, vol.9
, pp. 137-159
-
-
Arora, J.1
Elwakeil, O.2
Chahande, A.3
-
2
-
-
0030271834
-
Optimal learning in artificial neural networks: A review of theoretical results
-
M. Bianchini and M. Gori, "Optimal learning in artificial neural networks: A review of theoretical results", Neurocomputing, vol. 13, pp. 313-346, 1996.
-
(1996)
Neurocomputing
, vol.13
, pp. 313-346
-
-
Bianchini, M.1
Gori, M.2
-
3
-
-
0023979638
-
ALGORITHM 659 Implementing Sobol's quasirandom sequence generator
-
P. Bratley and B. Fox, "ALGORITHM 659 Implementing Sobol's quasirandom sequence generator", ACM Transactions on Mathematical Software, vol. 14, pp. 88-100, 1988.
-
(1988)
ACM Transactions on Mathematical Software
, vol.14
, pp. 88-100
-
-
Bratley, P.1
Fox, B.2
-
4
-
-
0027575229
-
Terminal repeller unconstrained subenergy tunneling (TRUST) for fast global optimization
-
B. Cetin, J. Barhen, and J. Burdick, "Terminal repeller unconstrained subenergy tunneling (TRUST) for fast global optimization", J. Opt. Theory and Appl., vol. 77, pp. 97-126, 1993.
-
(1993)
J. Opt. Theory and Appl.
, vol.77
, pp. 97-126
-
-
Cetin, B.1
Barhen, J.2
Burdick, J.3
-
5
-
-
84943257899
-
Global descent replaces gradient descent to avoid local minima problem in learning with ANN
-
B. Cetin, J. Burdick, and J. Barhen, "Global descent replaces gradient descent to avoid local minima problem in learning with ANN", in Proc. of IEEE Conf. on Neural Networks, vol. 2, pp. 836-842, 1993
-
(1993)
Proc. of IEEE Conf. on Neural Networks
, vol.2
, pp. 836-842
-
-
Cetin, B.1
Burdick, J.2
Barhen, J.3
-
6
-
-
51649099766
-
Neural network learning using low-discrepancy sequence
-
N. Foo, Ed., Springer-Verlag
-
I. Jordanov and R. Brown, "Neural network learning using low-discrepancy sequence", in Advanced Topics in Artificial Intelligence, N. Foo, Ed., Springer-Verlag, pp. 255-267, 1999.
-
(1999)
Advanced Topics in Artificial Intelligence
, pp. 255-267
-
-
Jordanov, I.1
Brown, R.2
-
7
-
-
0031698646
-
MARS - A multistart adaptive random search method for global constrained optimization in engineering applications
-
V. Litnetski and B. Abramzon, "MARS - a multistart adaptive random search method for global constrained optimization in engineering applications", Eng. Optimization, vol. 30, pp. 125-154, 1998.
-
(1998)
Eng. Optimization
, vol.30
, pp. 125-154
-
-
Litnetski, V.1
Abramzon, B.2
-
8
-
-
0002071152
-
Low-discrepancy sequences
-
H. Niederreiter, "Low-discrepancy sequences", J. of Number Theory, vol.30, pp. 51-70, 1988.
-
(1988)
J. of Number Theory
, vol.30
, pp. 51-70
-
-
Niederreiter, H.1
-
9
-
-
0023420912
-
Stochastic global optimization methods Part I: Clustering methods
-
A. Rinooy Kan and G. Timmer, "Stochastic global optimization methods Part I: Clustering methods", Mathematical programming, vol. 39, pp. 27-56, 1987.
-
(1987)
Mathematical Programming
, vol.39
, pp. 27-56
-
-
Rinooy Kan, A.1
Timmer, G.2
-
10
-
-
0000646059
-
Learning internal representation by error propagation
-
Cambridge, MA: MIT Press
-
D. Rumelhart, G. Hinton, and R. Williams, "Learning internal representation by error propagation", in Par. Distr. Proc.; Expl. in the Microstr. of Cognition, Cambridge, MA: MIT Press, pp. 318-362, 1986.
-
(1986)
Par. Distr. Proc.; Expl. in the Microstr. of Cognition
, pp. 318-362
-
-
Rumelhart, D.1
Hinton, G.2
Williams, R.3
-
11
-
-
0030104504
-
Global optimization for neural network training
-
Y. Shang and B. Wah, "Global optimization for neural network training", Computer, pp. 45-54, 1996.
-
(1996)
Computer
, pp. 45-54
-
-
Shang, Y.1
Wah, B.2
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