Abramson MA. (2004). Mixed variable optimization of a load-bearing thermal insulation system using a filter pattern search algorithm Optim Eng. 5
Angeline PJ, Saunders GM, Pollack JB. (1994). An evolutionary algorithm that constructs recurrent neural networks. IEEE transactions on neural networks. 5 [PubMed]
Blasco JA, Fueyo N, Dopazo C, Ballester J. (1999). Modelling the temporal evolution of a reduced combustion chemical system with an artificial neural network Combust Flame. 113
Blasco JA, Fueyo N, Dopazo C, Chen JY. (2000). A self-organizing-map approach to chemistry representation in combustion applications Combust Theory Modelling. 4
Blasco JA, Fueyo N, Dopazo C, Chen JY. (2000). An economical strategy for storage of chemical kinetics: Fitting in situ adaptive tabulation with artificial neural networks Proc Comb Institute. 28
Blasco JA, Fueyo N, Dopazo C, Chen JY, Larroya JC. (1999). Single-steptime-integrator of a methane-air chemical system using artificial neural networks Computers And Chemical Engineering. 23
Bornholdt S, Graudenz D. (1992). General asymmetric neural networks and structure design by genetic algorithms Neural Netw. 5
Chan CY, Tang KS, Man KF, Kwong S. (1995). Genetic structure for NN topology and weights optimization Proc 1st IEEE Intl Conf Genetic Algorithms in Engineering Systems: Innovations and Applications.
Christo FC, Masri AR, Nebot EM. (1996). Artificial neural network implementation of chemistry with PDF simulation of H2-CO2 flames Combust Flame. 106
Christo FC, Masri AR, Nebot EM, Pope SB. (1996). An integrated PDF-neural network approach for simulating turbulent reacting systems Proc Comb Institute. 26
Dennis JE, Abramson MA, Audet C. (2004). Generalized pattern searches with derivative information Math Program Ser B. 100
Dennis JE, Audet C. (2000). Pattern search algorithms for mixed variable programming SIAM J Optim. 11
Dennis JE, Audet C. (2003). Analysis of generalized pattern searches SIAM J Optim. 13
Dennis JE, Audet C. (2004). A pattern search filter method for nonlinear programming without derivatives SIAM J Optim. 14
Dennis JE, Audet C, Kokkolaras M. (2000). Mixed variable optimization of the number and composition of heat intercepts in a thermal insulation system Tech Rep TR00-21, Department of Computational and Applied Mathematics, Rice University.
Dennis JE et al. (1999). A rigorous framework for optimization of expensive functions by surrogates Structural Optim. 17
Dennis JE, Wang M, Marsden AL, Moin JE. (2004). Optimal aeroacoustic shape design using the surrogate management framework Optim Eng. 5
Fausett L. (1994). Fundamentals of Neural Networks.
Flemming F, Sadiki A, Janicka J. (2005). LES using artificial neural networks for chemistry representation Prog Comput Fluid Dynamics. 5
Frean M. (1990). The upstart algorithm: A method for constructing and training feedforward neural networks Neural Comput. 2
Hagan MT, Demuth HB, Beale M. (1996). Neural network design.
Haykin S. (1994). Neural Networks: A Comprehensive Foundation.
Jin Y, Husken M, Sendhoff B. (2005). Structure optimization of neural networks for evolutionary design optimization Soft Comput. 9
Koza JR, Rice JP. (1991). Genetic generation of both the weights and architecture for a neural network Proc IEEE Intl Joint Conf Neural Networks.
Lam SH, Goussis DA. (1988). Understanding complex chemical kinetics with computational singular perturbation Proc Comb Institute. 22
Liu Y, Yao X. (1996). Evolutionary design of artificial neural networks with different nodes Proc IEEE Conf Evolutionary Comput.
Mckay MD, Beckman RJ, Conover WJ. (1979). Comparison of three methods for selecting values of input variables in the analysis of output from a computer code Technometrics. 21
Miller G, Todd P, Hedge S. (1989). Designing neural networks using genetic algorithms Proc 3rd Intl Conf Genetic Algorithms.
Mozer MC, Smolensky P. (1989). Skeletonization: A technique for trimming the fat from a network via relevance assessment Connection Sci. 1
Nielsen HB, Lophaven SN, Sundergaard J. (2002). DACE: A Matlab Kriging toolbox version 2.0 Tech Rep IMM-TR-2002-12, Technical University of Denmark.
Owen A, Koehler J. (1996). Computer experiments: Design and analysis of experiments Handbook of statistics. 13
Park J, Hwang MW, Choi JK. (1997). Evolutionary projection neural networks Proc IEEE Conf Evolutionary Comput.
Peters N. (1984). Laminar diffusion flamelet models in non-premixed turbulent combustion Prog Energy Combust Sci. 10
Peters N. (2000). Turbulent combustion.
Pope SB. (1997). Computationally efficient implementation of combustion chemistry using in situ adaptive tabulation Combust Theory Modelling. 1
Pope SB, Maas U. (1992). Simplifying chemical kinetics: Intrinsic low dimensional manifolds in composition space Combust Flame. 88
Rubinstein RY. (1981). Simulation and the Monte Carlo method.
Sciandrone M, Lucidi S, Piccialli V. (2005). An algorithm model for mixed variable programming SIAM J Optim. 15
Serafini DB. (1998). A framework for managing models in nonlinear optimization of computationally expensive functions Unpublished doctoral dissertation, Rice University.
Smith GP et al. (1997). GRI-Mech 2.11 Available online at http:--www.me.berkeley.edu-gri-mech-.
Tonse SR, Moriarty NW, Brown NJ, Frencklach M. (1999). PRISM: Piecewise reusable implementation of solution mapping. An economical strategy for chemical kinetics Israel J Chem. 39
Torczon V. (1997). On the convergence of pattern search algorithms SIAM J Optim. 7
Yao X. (1999). Evolving artificial neural networks Proceedings Of The IEEE. 87