Macroeconomics modelling on UK GDP growth by neural computing

Li, Y. , Ng, K.C., Häußler, A., Chow, V. and Muscatelli, A. (1995) Macroeconomics modelling on UK GDP growth by neural computing. In: IFAC/IFIP/IFORS/SEDC Symp. Modelling and Control of National and Regional Economies, Gold Coast, Australia, 2-5 July 1995,

88958.pdf - Accepted Version



This paper presents multilayer neural networks used in UK gross domestic product estimation. These networks are trained by backpropagation and genetic algorithm based methods. Different from backpropagation guided by gradients of the performance, the genetic algorithm directly evaluates the performance of multiple sets of neural networks in parallel and then uses the analysed results to breed new networks that tend to be better suited to the problems in hand. It is shown that this guided evolution leads to globally optimal networks and more accurate results, with less adjustment of the algorithm needed.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Chow, Mr Victor and Muscatelli, Professor Anton and Li, Professor Yun
Authors: Li, Y., Ng, K.C., Häußler, A., Chow, V., and Muscatelli, A.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy

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