-
2
-
-
0021370966
-
Dynamic Recrystallization: Mechanical and Microstructural Considerations
-
2
-
T. Sakai, J.J. Jonas 1984 Dynamic Recrystallization: Mechanical and Microstructural Considerations. Acta Metal. 32(2):89-209
-
(1984)
Acta Metal.
, vol.32
, pp. 89-209
-
-
Sakai, T.1
Jonas, J.J.2
-
3
-
-
34047114404
-
Kinetics, Mechanism and Modelling of Microstructural Evolution during Thermomechanical Processing of a 15Cr-15Ni-2.2Mo-Ti Modified Austenitic Stainless Steel
-
S. Mandal, P.V. Sivaprasad, R.K. Dube 2006 Kinetics, Mechanism and Modelling of Microstructural Evolution During Thermomechanical Processing of a 15Cr-15Ni-2.2Mo-Ti Modified Austenitic Stainless Steel. J. Mater. Sci. 42:2724-2734
-
(2006)
J. Mater. Sci.
, vol.42
, pp. 2724-2734
-
-
Mandal, S.1
Sivaprasad, P.V.2
Dube, R.K.3
-
4
-
-
84935612807
-
Modeling Microstructural Development during Hot Rolling
-
C.M. Sellars 1990 Modeling Microstructural Development During Hot Rolling. Mater. Sci. Technol. 15:1072
-
(1990)
Mater. Sci. Technol.
, vol.15
, pp. 1072
-
-
Sellars, C.M.1
-
5
-
-
0026817291
-
Physical Modeling of Materials Problem
-
M.F. Ashby 1992 Physical Modeling of Materials Problem. Mater. Sci. Technol. 8:102
-
(1992)
Mater. Sci. Technol.
, vol.8
, pp. 102
-
-
Ashby, M.F.1
-
7
-
-
0024047786
-
Recovery and Recrystallization of Polycrystalline Nickel after Hot Working
-
7
-
T. Sakai, M. Ohashi, K. Chiba, J.J. Jonas 1988 Recovery and Recrystallization of Polycrystalline Nickel After Hot Working. Acta Metal. 36(7):1781-1790
-
(1988)
Acta Metal.
, vol.36
, pp. 1781-1790
-
-
Sakai, T.1
Ohashi, M.2
Chiba, K.3
Jonas, J.J.4
-
8
-
-
23044469560
-
Effect of Initial Texture on the Recrystallization Texture of Cold Rolled AA 5182 Aluminum Alloy
-
1-2
-
W.C. Liu, J.G. Morris 2005 Effect of Initial Texture on the Recrystallization Texture of Cold Rolled AA 5182 Aluminum Alloy. Mater. Sci. Eng. A 402(1-2):215-227
-
(2005)
Mater. Sci. Eng. A
, vol.402
, pp. 215-227
-
-
Liu, W.C.1
Morris, J.G.2
-
10
-
-
0032022579
-
A Comparison between the Back-Propagation and Counter-Propagation Networks in the Modeling of the TIG Welding Process
-
1-3
-
S.C. Juang, Y.S. Tarang, H.R. Lii 1998 A Comparison Between the Back-Propagation and Counter-Propagation Networks in the Modeling of the TIG Welding Process. J. Mater. Process. Technol. 75(1-3):54-62
-
(1998)
J. Mater. Process. Technol.
, vol.75
, pp. 54-62
-
-
Juang, S.C.1
Tarang, Y.S.2
Lii, H.R.3
-
11
-
-
0033078679
-
Using Neural Networks to Predict Parameters in the Hot Working of Aluminum Alloys
-
1-3
-
M.S. Chun, J. Biglou, J.G. Lenard, J.G. Kim 1999 Using Neural Networks to Predict Parameters in the Hot Working of Aluminum Alloys. J. Mater. Process. Technol. 86(1-3):245-251
-
(1999)
J. Mater. Process. Technol.
, vol.86
, pp. 245-251
-
-
Chun, M.S.1
Biglou, J.2
Lenard, J.G.3
Kim, J.G.4
-
13
-
-
0028466750
-
Advanced supervised learning in multi-layer perceptrons - From backpropagation to adaptive learning algorithms
-
M. Riedmiller, Advanced Supervised Learning in Multi-layer Perceptrons - From Backpropagation to Adaptive Learning Algorithms, Special Issue on Neural Networks, Int. J. of Comp. Stand. Inter., 1994, 16, p 265-278
-
(1994)
Special Issue on Neural Networks, Int. J. of Comp. Stand. Inter.
, vol.16
, pp. 265-278
-
-
Riedmiller, M.1
-
14
-
-
0025593679
-
SuperSAB: Fast Adaptive Back Propagation with Good Scaling Properties
-
5
-
T. Tollenaere 1990 SuperSAB: Fast Adaptive Back Propagation with Good Scaling Properties, Neural Network 3(5):561-573
-
(1990)
Neural Network
, vol.3
, pp. 561-573
-
-
Tollenaere, T.1
-
15
-
-
51249174335
-
Effect of Stacking Fault Energy on the Dynamic Recrystallization during Hot Working of FCC Metals: A Study Using Processing Maps
-
Y.V.R.K. Prasad and N. Ravichandran (1991) Effect of Stacking Fault Energy on the Dynamic Recrystallization During Hot Working of FCC Metals: A Study Using Processing Maps, Bull. Mater. Sci. 14:1241-1248
-
(1991)
Bull. Mater. Sci.
, vol.14
, pp. 1241-1248
-
-
Prasad, Y.V.R.K.1
Ravichandran, N.2
-
16
-
-
33746894601
-
Constitutive flow behaviour of austenitic stainless steels under hot deformation: Artificial neural network modeling to understand
-
S. Mandal, P.V. Sivaprasad, S. Venugopal, and K.P.N. Murthy, Constitutive Flow Behaviour of Austenitic Stainless Steels Under Hot Deformation: Artificial Neural Network Modeling to Understand, Evaluate and Predict. Model. Simul. Mater. Sci. Eng., 2006, 14, p 1053
-
(2006)
Evaluate and Predict. Model. Simul. Mater. Sci. Eng.
, vol.14
, pp. 1053
-
-
Mandal, S.1
Sivaprasad, P.V.2
Venugopal, S.3
Murthy, K.P.N.4
-
18
-
-
0002342092
-
Necklace Formation during Dynamic Recrystallization: Mechanisms and Impact on Flow Behavior
-
1
-
D. Ponge, G. Gottstein 1998 Necklace Formation During Dynamic Recrystallization: Mechanisms and Impact on Flow Behavior. Acta Mater. 46(1):69-80
-
(1998)
Acta Mater.
, vol.46
, pp. 69-80
-
-
Ponge, D.1
Gottstein, G.2
-
19
-
-
0032058295
-
Nucleation Mechanisms of Dynamic Recrystallization in Austenitic Steel Alloy 800H
-
12
-
E. Brunger, X. Wang, G. Gottstein 1998 Nucleation Mechanisms of Dynamic Recrystallization in Austenitic Steel Alloy 800H. Scripta Mater. 38(12):1843-1849
-
(1998)
Scripta Mater.
, vol.38
, pp. 1843-1849
-
-
Brunger, E.1
Wang, X.2
Gottstein, G.3
-
20
-
-
0024880831
-
Multilayer Feed Forward Networks are Universal Approximations
-
5
-
K. Hornik, M. Stinchcombe, H. White 1989 Multilayer Feed Forward Networks are Universal Approximations. Neural Network 2(5):359-366
-
(1989)
Neural Network
, vol.2
, pp. 359-366
-
-
Hornik, K.1
Stinchcombe, M.2
White, H.3
-
21
-
-
0037102687
-
Illuminating the "black Box": A Randomization Approach for Understanding Variable Contributions in Artificial Neural Networks
-
1-2
-
J.D. Olden, D.A. Jackson 2002 Illuminating the "Black Box": A Randomization Approach for Understanding Variable Contributions in Artificial Neural Networks. Ecol. Model. 154(1-2):135-150
-
(2002)
Ecol. Model.
, vol.154
, pp. 135-150
-
-
Olden, J.D.1
Jackson, D.A.2
-
22
-
-
0037442845
-
Review and Comparison of Methods to Study the Contribution of Variables in Artificial Neural Network Models
-
3
-
M. Gevrey, I. Dimopoulos, S. Lek 2003 Review and Comparison of Methods to Study the Contribution of Variables in Artificial Neural Network Models. Ecol. Model. 160 (3):249-264
-
(2003)
Ecol. Model.
, vol.160
, pp. 249-264
-
-
Gevrey, M.1
Dimopoulos, I.2
Lek, S.3
-
23
-
-
3242721368
-
An Accurate Comparison of Methods for Quantifying Variable Importance in Artificial Neural Networks Using Simulated Data
-
3-4
-
J.D. Olden, M.K. Joy, R.G. Death 2004 An Accurate Comparison of Methods for Quantifying Variable Importance In Artificial Neural Networks Using Simulated Data. Ecol. Model. 178(3-4):389-397
-
(2004)
Ecol. Model.
, vol.178
, pp. 389-397
-
-
Olden, J.D.1
Joy, M.K.2
Death, R.G.3
-
24
-
-
0001867238
-
Interpreting Neural Network Connection Weights
-
7
-
G.D. Garson 1991 Interpreting Neural Network Connection Weights. Artif. Intell. Expert 6(7):47-51
-
(1991)
Artif. Intell. Expert
, vol.6
, pp. 47-51
-
-
Garson, G.D.1
-
25
-
-
0029223565
-
Back-Propagation Neural Networks for Modelling Complex Systems
-
A.T.C. Goh 1995 Back-Propagation Neural Networks for Modelling Complex Systems. Artif. Intell. Eng. 9:143-151
-
(1995)
Artif. Intell. Eng.
, vol.9
, pp. 143-151
-
-
Goh, A.T.C.1
|