Differential Evolution Training Algorithm for Feed-Forward Neural Networks
 Min Liang,et al. Fast learning algorithms for multi-layered feedforward neural network , 1994, Proceedings of National Aerospace and Electronics Conference (NAECON'94).
 Steven Doyle,et al. Automated mirror design using an evolution strategy , 1999 .
 Manfred M. Fischer,et al. A global search procedure for parameter estimation in neural spatial interaction modelling , 1999 .
 C. Charalambous,et al. Conjugate gradient algorithm for efficient training of artifi-cial neural networks , 1990 .
 X. Yao. Evolving Artificial Neural Networks , 1999 .
 R. W. Derksen,et al. Differential Evolution in Aerodynamic Optimization , 1999 .
 A. Hamler,et al. Analysis of iron loss in interior permanent magnet synchronous motor over a wide-speed range of constant output power operation , 2000 .
 S. P. Day,et al. A stochastic training technique for feed-forward neural networks , 1990, 1990 IJCNN International Joint Conference on Neural Networks.
 Jarmo T. Alander,et al. An Indexed Bibliography of Genetic Algorithms , 1995 .
 W. Land,et al. A new training algorithm for the general regression neural network , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.
 R. Storn,et al. Differential evolution a simple and efficient adaptive scheme for global optimization over continu , 1997 .
 Feng-Sheng Wang,et al. Multiobjective parameter estimation problems of fermentation processes using a high ethanol tolerance yeast , 2000 .
 Rainer Storn,et al. Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..
 George D. Magoulas,et al. Hybrid methods using evolutionary algorithms for on-line training , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).
 Lutz Prechelt. Some notes on neural learning algorithm benchmarking , 1995, Neurocomputing.
 Mohammad Bagher Menhaj,et al. Training feedforward networks with the Marquardt algorithm , 1994, IEEE Trans. Neural Networks.
 Chris Aldrich,et al. Combinatorial evolution of regression nodes in feedforward neural networks , 1999, Neural Networks.
 Ivan Zelinka,et al. Mechanical engineering design optimization by differential evolution , 1999 .
 Kay Hameyer,et al. Optimization of radial active magnetic bearings using the finite element technique and the differential evolution algorithm , 2000 .
 T.,et al. Training Feedforward Networks with the Marquardt Algorithm , 2004 .
 Riccardo Poli,et al. New Ideas In Optimization , 1999 .
 Lutz Prechelt. PROBEN 1 - a set of benchmarks and benchmarking rules for neural network training algorithms , 1994 .
 Martin F. Møller,et al. Efficient Training of Feed-Forward Neural Networks , 1993 .
 Nathalie Japkowicz,et al. Adaptability of the backpropagation procedure , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).