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Research Journal of Pharmacy and Technology
Year : 2017, Volume : 10, Issue : 1
First page : ( 87) Last page : ( 90)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2017.00021.X

Stock Price Prediction using Rule Based Genetic Algorithm Approach

Srinivasan N1,*, Lakshmi C2

1Research Scholar, School of Computing, Sathyabama University, Chennai, Tamil Nadu, India

2Professor, Department of Software Engineering, SRM University, Chennai, Tamil Nadu, India

*Corresponding Author E-mail: srinijyothish@gmail.com

Online published on 29 April, 2017.


Securities trade data is a high dimensional time course of action cash related data that positions exceptional computational challenges. Stock data is variable with respect to time, suspecting the future example of the expenses is a trying task. The segments that effect the consistency of stock data can't be judged as the same variables may affect the estimation of the stock always. We propose a data burrowing approach for the desire of the advancement of securities trade. It consolidates using the innate estimation for pre taking care of and a cross breed packing strategy of Hierarchical gathering and Fuzzy C-Means for clustering. The genetic figuring helps in dimensionality diminish and packing makes highlight vectors that help with estimate.



Fuzzy, C-Means, Stock, Prediction, Genetic Algorithm.


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