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A model auto-selection financial data simulation software using neuron-adaptive feedforward neural networks

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2 Author(s)
Shuxiang Xu ; Dept. of Comput. & Inf. Syst., Western Sydney Univ., Campbelltown, NSW, Australia ; Ming Zhang

In this paper, a model auto-selection (MAS) neural network financial data simulation software, MASFinance, has been developed for use on UNIX. The core of the software is a neuron-adaptive feedforward neural network (NANN) and a learning algorithm that combines steepest descent rule with a pruning method, and the software serves as a tool for selecting a near optimal neural network simulation model for economic data. Our test outcomes show that, for a given set of real life financial data, MASFinance can automatically choose a near optimal simulation model (a NANN with a near optimal neuron activation function and near optimal numbers of hidden layers and units) and then simulates the data with a root-mean-squared error of less than 5%

Published in:

Neural Networks, 1999. IJCNN '99. International Joint Conference on  (Volume:6 )

Date of Conference:

Jul 1999

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