Learning internal

Rumelhart, D.E., Hinton, G.E. and Williams, R.J. (1986) Learning internal representations by error propagation. In Parallel Distributed Processing, Rumelhart, D.E. and McClelland, J.L. (eds.), M.I.T. Press, Cambridge, Mass. 

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D.E. Rumelhart, J.L. McClelland Parallel Distributed Processing Explorations in the microstructure of cognition Vol.l Learning internal representations by error propagation, MIT Press, Cambridge (MA, USA) 1986... 

McNulty, A., Northern Business Unit Inert Gas Lessons Learned , Internal Safety Memo, Foinaven Delivery Unit, Northern Business Unit, BP, 29 March, 2001. 

Implicit in this paradigm is the notion that the cybernetic sequence is embedded in the neural, knowledge base, and learned internal models and can be mapped by defining the differential change in mental, disciplinary structural, and expert models. 

Incident Tracking and Analysis Database of incident information Periodic review of data Identification of trends in data Share lessons learned internally and, as appropriate, externally Proactively involve all parties to prevent future occurrences... 

Reiner, M., Gilbert, J. (2000). Epistemological resources for thought experimentation in science learning. International Journal of Science Education, 22(5), 489-506. 

Varshneya AK. Chemical strengthening of glass lessons learned and yet to be learned. International Journal of Applied Glass Science 2010 1(2) 131-142. 

Carroll, J. M., and Mack, R. L. (1985), Metaphor, Computing Systems, and Active Learning, International Journal of Man-Machine Studies, Vol. 22, pp. 39-57. 

Kotsiantis, S. B., KaneUopoulos, D. and Pintelas, P. E., 2006. Data preprocessing for supervised learning. International Journal of Electrical and Computational Engineering, 1(2), 111-117. 

Tuan, H. L., Chin, C. C., Shieh, S. H. (2005). The development of a questionnaire to measure students motivation towards science learning. International Journal of Science Education, 27, 639-654. 

Boud, D., Rooney, D. Solomon, N. (2009) Talking up learning at work Cautionary tales in co-opting learning. International Journal of Lifelong Education, 28 (3), 323-334. 

Abbeel, R, A. Coates, and A.Y. Ng. 2010. Autonomous helicopter aerobatics through apprenticeship learning. International Journal of Robotics Research 29(7). doi 10.1177/0278364910371999. 

RQey, D. M., Qaris, L. (2008). Developing and assessing students capacity for lifelong learning. International Journal of Engineering Education, 24(5), 906-916. 

Morrison, J.B., Tversky, B., Betrancourt, M. Animation Does It Facilitate Learning International Journal of Human Computer Studies 57(4), 247-262 (2002)... 

Rumelhart, D. E. Hinton, G. Williams, R. J. Learning Internal Representations by Error propagation in Parallel Distributed Processing Explorations in the Microstructure of Cognition, vol 1 ISBNIO 026268053 MIT Press Cambridge, 1986. 

An ANN is a black-box model which produces certain output data as a response to a specific combination of input data. It can be trained to learn internal relationships and predict system behavior without any physical equations. ANNs consist of neurons gathered into layers. Information is delivered to the neurons by dendrites and the activation function is realized (by the nucleus). Then modified information is transferred forward by the axon and synapses (see Fig. 5.15) to other neurons. 

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