Abstract
Neural networks, and related statistical pattern recognition techniques, appear to be well suited to the solution of a wide range of monitoring and diagnostic problems. In many applications, it is difficult or impossible to perform first-principles modelling of the system under consideration. If, however, sufficiently large quantities of labelled training data can be made available, then a statistical approach becomes feasible.
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References
CM Bishop and GD James (1993) Analysis of multiphase flows using dual-energy gamma densitometry and neural networks’, Nuclear Instruments and Methods in Physics Research A327 (1993) 580.
MS Abouelwafa and EJM Kendall, J. Phys. E: Sci. Instrum., 13 (1980) 341.
K Rafa, T Tomoda and R Ridley Proc. Energy Sources Technology Conference and Exhibition, ASME (1989) 89-Pet-7.
M S Beck and A Plaskowski, Cross Correlation Flowmeters, (Adam Hilger, Bristol, 1987).
JS Watt, HW Zastawny, MD Rebgetz, PE Hartley and WK Ellis, Nuclear Techniques in the Exploration and Exploitation of Energy and Mineral Resources, (IAEA, Vienna, 1991) p. 481.
CM Bishop, invited review article: Neural Networks and their Applications to be published in Reviews of Scientific Instruments (1993).
CM Bishop, Neural Networks for Pattern Recognition, (Oxford University Press, 1994).
CM Bishop ‘Exact calculation of the Hessian matrix for the multilayer perceptron’ Neural Computation, 4 (1992) 494–501.
CM Bishop ‘Improving the generalization properties of radial basis function neural networks’ Neural Computation 3 (1991) 579–588.
C M Bishop ‘Curvature Driven Smoothing: A Learning Algorithm for Feedforward Networks’, to be published in IEEE Transactions on Neural Networks (1993).
A R Webb (1991) ‘Functional Approximation by Feedforward Networks: A Least-squares Approach to Generalisation’ RSRE Memorandum 4453, R.S.R.E., St. Andrews Road, Malvern, Worcs, WR14 3PS, U.K.
R O Duda and P Hart, Pattern Classification and Scene Analysis (John Wiley, New York, 1973).
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© 1995 Springer Science+Business Media New York
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Bishop, C.M. (1995). Multiphase flow monitoring in oil pipelines. In: Murray, A.F. (eds) Applications of Neural Networks. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2379-3_6
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DOI: https://doi.org/10.1007/978-1-4757-2379-3_6
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-5140-3
Online ISBN: 978-1-4757-2379-3
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