%0 Journal Article %1 Mundada_2015 %A Mundada, Dhiraj %A Chhaparwal, Gaurav %A Chaudhari, Sachin %A Bhamare, Trupti %D 2015 %I Auricle Technologies, Pvt., Ltd. %J International Journal on Recent and Innovation Trends in Computing and Communication %K Artificial Back Intelligence Learning Machine Networks Neural Stock market propagation %N 4 %P 2217--2219 %R 10.17762/ijritcc2321-8169.150498 %T Stock Value Prediction System %U http://dx.doi.org/10.17762/ijritcc2321-8169.150498 %V 3 %X The use of artificial neural network is gaining popularity in the research field. Neural network consist of interconnected neurons which deciphers value by using input data by feeding network values. The main aim of our project is to use backpropagation process to predict the future value.Stock market prediction models are the most challenging fields in computer science. The aim of this project is implementation of neural networks with back propagation algorithm for stock value prediction .A neural network is a powerful data-modeling tool that is able to capture and represent complex input/output relationships. We apply Data mining technology to the stock in order to research the trend of the market. Our proposed system provides methods to develop machine learning stock market predictor based on Neural Networks using Back propagationalgorithm, with intent of improving the accuracy. In this paper we have used data mining process along with artificial neural network networking to predict the future value of the stock. This paper overcomes the all traditional statistical methods of the stock market value prediction.

@article{Mundada_2015, abstract = {The use of artificial neural network is gaining popularity in the research field. Neural network consist of interconnected neurons which deciphers value by using input data by feeding network values. The main aim of our project is to use backpropagation process to predict the future value.Stock market prediction models are the most challenging fields in computer science. The aim of this project is implementation of neural networks with back propagation algorithm for stock value prediction .A neural network is a powerful data-modeling tool that is able to capture and represent complex input/output relationships. We apply Data mining technology to the stock in order to research the trend of the market. Our proposed system provides methods to develop machine learning stock market predictor based on Neural Networks using Back propagationalgorithm, with intent of improving the accuracy. In this paper we have used data mining process along with artificial neural network networking to predict the future value of the stock. This paper overcomes the all traditional statistical methods of the stock market value prediction.}, added-at = {2015-08-26T09:54:33.000+0200}, author = {Mundada, Dhiraj and Chhaparwal, Gaurav and Chaudhari, Sachin and Bhamare, Trupti}, biburl = {https://www.bibsonomy.org/bibtex/21aa695c8d0dcec29512a8804643db001/ijritcc}, doi = {10.17762/ijritcc2321-8169.150498}, interhash = {16c3b509272d85963d0ddc3820fc4bdb}, intrahash = {1aa695c8d0dcec29512a8804643db001}, journal = {International Journal on Recent and Innovation Trends in Computing and Communication}, keywords = {Artificial Back Intelligence Learning Machine Networks Neural Stock market propagation}, month = {april}, number = 4, pages = {2217--2219}, publisher = {Auricle Technologies, Pvt., Ltd.}, timestamp = {2015-08-26T09:54:33.000+0200}, title = {Stock Value Prediction System}, url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150498}, volume = 3, year = 2015 }