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@article{156037,
        author = {Padmavathi M and Rampur Srinath},
        title = {Analyzing Stock Price Using Artificial Neural Network},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {2},
        pages = {614-617},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=156037},
        abstract = {Presently, a huge amount of money has been invested into stock markets due to its high demand in the running economy. All over the nation economies have been favored to be associated with their achievements in stock markets. Alongside, trading in today's world has become so popular and accessible to any common man and to investors who plan their capitals ahead.
Artificial neural networks (ANN) is a branch of Artificial Intelligence (AI) which actually copies the biological neural signals, here helps us to predict samples required and prepare the information model. Neural networks in today's world are considered as one the most important higher-ranking approaches to bifurcate incognito or unidentified samples in input methods that are required to which are needed for the inventory market. Many algorithms such as Feedforward neural networks were adopted to study the way humans make predictions and implement the same in the model. 
Backpropagation schooling algorithm provides additional support in the process.},
        keywords = {Machine learning, Artificial Neural Networks, Stock Price Prediction},
        month = {},
        }