Press "Enter" to skip to content

Artificial Neural Network Modelling - download pdf or read online

By Subana Shanmuganathan, Sandhya Samarasinghe

ISBN-10: 3319284932

ISBN-13: 9783319284934

ISBN-10: 3319284959

ISBN-13: 9783319284958

This booklet covers theoretical features in addition to fresh leading edge purposes of man-made Neural networks (ANNs) in typical, environmental, organic, social, commercial and automatic systems.

It offers contemporary result of ANNs in modelling small, huge and complicated platforms less than 3 different types, specifically, 1) Networks, constitution Optimisation, Robustness and Stochasticity 2) Advances in Modelling organic and Environmental Systems and three) Advances in Modelling Social and monetary Systems. The e-book goals at serving undergraduates, postgraduates and researchers in ANN computational modelling.

Show description

Read Online or Download Artificial Neural Network Modelling PDF

Best intelligence & semantics books

New PDF release: Singularity Theory and Its Applications: Warwick 1989:

A workshop on Singularities, Bifuraction and Dynamics was once held at Warwick in July 1989, as a part of a year-long symposium on Singularity idea and its purposes. The lawsuits fall into halves: quantity I ordinarily on connections with algebraic geometry and quantity II on connections with dynamical structures conception, bifurcation thought and purposes within the sciences.

Download e-book for iPad: Problem-Solving Methods: Understanding, Description, by Dieter Fensel

This publication offers a conception, a proper language, and a pragmatic method for the specification, use, and reuse of problem-solving equipment. The framework constructed via the writer characterizes knowledge-based structures as a specific kind of software program structure the place the purposes are constructed through integrating familiar activity necessities, challenge fixing equipment, and area types: this strategy turns wisdom engineering right into a software program engineering self-discipline.

Download PDF by Johanna D. Moore: Participating in explanatory dialogues : interpreting and

Whereas a lot has been written in regards to the components of textual content iteration, textual content making plans, discourse modeling, and person modeling, Johanna Moore's booklet is without doubt one of the first to take on modeling the complicated dynamics of explanatory dialogues. It describes an explanation-planning structure that permits a computational method to take part in an interactive discussion with its clients, targeting the information buildings approach needs to construct in an effort to tricky or make clear past utterances, or to respond to follow-up questions within the context of an ongoing discussion.

Extra resources for Artificial Neural Network Modelling

Sample text

9 Weighted hidden neuron activation for the random data samples 2 and 3 and corresponding correlation matrices 26 S. Samarasinghe y (a) (b) 200 150 Neu - 2 100 -2 - 50 8 6 4 2 Neu - 3 50 -4 y Neu - 1 2 4 x Neu - 4 Neu - 5 -4 - 100 -2 -2 Neu - 1 Neu - 2 2 4 x Neu - 3 Fig. 10 Weighted hidden neuron activation of a 3-neuron a and 5-neuron b networks and corresponding correlation matrices Figure 10 illustrate convincingly that the redundant neurons can be identified by their high correlation. By removing redundant neurons, both networks are left with 2 (optimum number) of neurons.

Neurocomputing 48, 937–955 (2002) 10. M. Hagiwara, Removal of hidden units and weights for backpropagation networks. Proc. Int. Joint Conf. Neural Networks 1, 351–354 (1993) 11. F. Aires, Neural network uncertainty assessment using Bayesian statistics with application to remote sensing: 1. Network weights. J. Geophys. Res. 109, D10303 (2004). 1029/ 2003JD004173 12. F. Aires, Neural network uncertainty assessment using Bayesian statistics with application to remote sensing: 2. Output Error. J. Geophys.

Haykin, Neural Networks: A comprehensive Foundation, 2nd edn. (Prentice Hall Inc, New Jersey, USA, 1999) 4. R. Reed, Pruning algorithms-A survey. IEEE Trans. Neural Networks 4, 740–747 (1993) 5. Y. S. A. Solla, Optimal brain damage, in Advances in Neural Information Processing (2), ed. S. Touretzky (1990), pp. 598–605 6. B. G. J. Wolff, Optimal brain surgeon and general network pruning. IEEE International Conference on Neural Networks, vol. 1, (San Francisco, 1992), pp. 293–298 7. B. G. Stork, Second-order derivatives for network pruning: Optimal brain surgeon, in Advances in Neural Information Processing Systems, vol.

Download PDF sample

Artificial Neural Network Modelling by Subana Shanmuganathan, Sandhya Samarasinghe


by Thomas
4.4

Rated 4.62 of 5 – based on 28 votes