Multi Layer Feed Forward Neural Network Knowledge Base to Future Stock Market Prediction
G. Sundar1, K. Satyanarayana2
1G. Sundar, Research Scholar, Bharath University, Chennai, India.
2Dr. K. Satyanarayana, Research Supervisor, Bharath University, Chennai.Principal & Prof, Dept. of Computer Science, Sindhi College, Chennai. India
Manuscript received on 15 September 2019 | Revised Manuscript received on 23 September 2019 | Manuscript Published on 11 October 2019 | PP: 1061-1075 | Volume-8 Issue-11S September 2019 | Retrieval Number: K121809811S19/2019©BEIESP | DOI: 10.35940/ijitee.K1218.09811S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Stock price prediction is always a most challenging task. Artificial Neural Network prediction clears the stock price prediction challenge by forming the training set. By using the past information as the network input, one can predict the expected output of the network. In order to predict the expected result as the accurate we add multi-layer perceptron to the knowledge set we formed from the past historical data available in the nifty NSE and Sensex BSE. This paper proves that proposing the learning knowledge set using multilayer neural network will predict the accurate closing price of future stock in stock market.
Keywords: Artificial Neural Network (ANN), Knowledge set, Multilayer neural perceptron network, stock market.
Scope of the Article: Regression and Prediction