By I. M. Mujtaba, Mehboob A. Hussain
This quantity is a follow-up to the IChemE symposium on "Neural Networks and different studying Technologies", held at Imperial university, London, in may well 1999. The curiosity proven by means of the contributors, specifically these from the undefined, has been instrumental in generating the booklet. The papers were written by means of participants to the symposium and specialists within the box from worldwide. They current the entire very important points of neural community usage in addition to exhibit the flexibility of neural networks in a variety of elements of strategy engineering difficulties - modelling, estimation, keep watch over, optimization and business purposes.
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Extra info for Application of Neural Networks and Other Learning Technologies in Process Engineering
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Two center selection techniques that are based on this approach are kmeans clustering and linear regression methods. The k-means clustering algorithm (Moody and Darken, 1989; Leonard and Kramer, 1991; Chen, et al, 1992) partitions the data set used for identification into subsets of clusters, and finds a set of cluster centers. The cluster centers are used as the centers of the RBF nodes in the hidden layer of the network. , the number of hidden nodes in the network), M, must be specified. The data are partitioned such that each data point in the network input space defined by x(/) in Eq.
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Application of Neural Networks and Other Learning Technologies in Process Engineering by I. M. Mujtaba, Mehboob A. Hussain