Fast learning

Moody, J and Darken, C. J., Fast learning in networks of locally-tuned processing units. Neural Comput. 1, 281 (1989). 

A. Sankar and R. Mammone, A fast learning algorithm for tree neural networks. In Proc. 1990 Conf. on Information Sciences and Systems, Princeton, NJ, 1990, pp. 638-642. 

The beginning of the possible market introduction of hydrogen passenger cars in the most optimistic scenarios is around 2015, which is also in line with the implementation plan of the European Hydrogen and Fuel Cell Technology Platform (HFP, 2007). The Reference scenario features high policy support, fast learning, concentrated users, early network and no country-specific bounds. 

The scenarios high , medium and low penetration correspond to the scenarios very high policy support fast learning , high policy support fast learning and moderate policy support moderate learning , respectively, as used in Chapter 14. a Demonstration vehicles and fleets only. 

Moderate policy support, moderate learning High policy support, fast learning... 

Figure 19.10. Impact on reduction of fine dust emissions as a result of the introduction of hydrogen in road transport comparison of the high-support and fast-learning scenario with the baseline scenario scenario data are taken from Mattucci (2007).

Fahlman, S. E. (1988). Fast learning variations on back-propagation An empirical study. In Proceedings of the 1988 Connectionist Models Summer School (ed. Hinton, G. E., Sejnowski, T. J. Touretzky, D. S.), pp. 38-51. Morgan Kaufmann, San Mateo, CA. 

Moody, J. (1989), Fast Learning in Multi-Resolution hierarchies, Advances in Neural Information Processing, Vol. 1, pp. 29-39. 

Fast learning curve, as discussed above, has led to rapid improvements in technology, management and, therefore, product quality. 

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