Selvan Simon1 and Arun Raoo2,1SNDT Women's University, India and 2National Institute of Industrial Engineering, India
ABSTRACT
Globalization has made the stock market prediction (SMP) accuracy more challenging and rewarding for the researchers and other participants in the stock market. Local and global economic situations along with the company’s financial strength and prospects have to be taken into account to improve the prediction accuracy. Artificial Neural Networks (ANN) has been identified to be one of the dominant data mining techniques in stock market prediction area. In this paper, we survey different ANN models that have been experimented in SMP with the special enhancement techniques used with them to improve the accuracy. Also, we explore the possible research strategies in this accuracy driven ANN models.
KEYWORDS
Artificial Neural Networks, Multilayer Perceptron, Back Propagation, Stock market prediction & Prediction accuracy.
Original Source URL: https://airccse.org/journal/ijsc/papers/3211ijsc03.pdf
https://airccse.org/journal/ijsc/current2012.html
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#ArtificialNeuralNetworks #multilayerperceptron #Backpropagation #stockmarketprediction #predictionaccuracy
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