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Research Article

Optimizing The Architecture Of Artificial Neural Networks In Predicting Indian Stock Prices


Author(s): A. Victor Devadoss , T. Antony Alphonnse Ligori
Affiliation: Head and Associate Professor, Department of Mathematics, Loyola College, Chennai, India.
Year of Publication: 2014
Source: International Journal of Computing Algorithm
     
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Citation: A. Victor Devadoss, T. Antony Alphonnse Ligori. "Optimizing The Architecture Of Artificial Neural Networks In Predicting Indian Stock Prices." International Journal of Computing Algorithm 3.3 (2014): 316-323.

Abstract:
In forecasting, the design of an Artificial Neural Network ANN is a non-trivial task and choices incoherent with the problem could lead to instability of the network. So a Genetic Algorithm GA approach is used to find an optimal topology for the prediction. This paper presents a novel approach to Optimization of ANN topology that uses GA for the forecasting of Indian Stock Prices under Bombay Stock Exchange. After determining the optimum network determined by GA, forecasting of the stock prices is found by implementing MATLAB tool.


Keywords Artificial Neural Network ANN; Genetic Algorithm GA; Optimization.


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@article{Opt1486633, author = {A. Victor Devadoss,T. Antony Alphonnse Ligori}, title = {Optimizing The Architecture Of Artificial Neural Networks In Predicting Indian Stock Prices}, journal={International Journal of Computing Algorithm}, volume={3}, issue={3}, issn = {2278-2397}, year = {2014}, publisher = {Scholarly Citation Index Analytics-SCIA}

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