UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 12 | Issue 9 | September 2025

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Published in:

Volume 10 Issue 5
May-2023
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2305936


Registration ID:
516592

Page Number

i862-i865

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Title

Prediction of Stock Market Based On LSTM

Abstract

The stock market is inherently unpredictable because stock values are constantly changing due to a variety of reasons, making stock forecasting a challenging and incredibly complex endeavor. Today's investors are intensely engaged in the market and require quick access to precise information. Stock price prediction is a research area with rapidly expanding technology advancements. recognizing the stock's pattern. Predicting a company's future growth and financial development will be very helpful in determining its stock price. This focuses on the use of the Long Short-Term Memory (LSTM) Recurrent neural network (RNN) based machine learning method. To forecast stock values, use LSTM.

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"Prediction of Stock Market Based On LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.i862-i865, May-2023, Available :http://www.jetir.org/papers/JETIR2305936.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Prediction of Stock Market Based On LSTM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppi862-i865, May-2023, Available at : http://www.jetir.org/papers/JETIR2305936.pdf

Publication Details

Published Paper ID: JETIR2305936
Registration ID: 516592
Published In: Volume 10 | Issue 5 | Year May-2023
DOI (Digital Object Identifier):
Page No: i862-i865
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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