Advanced Stock Price Prediction: A Comprehensive Study Using LSTM And GRU Based Machine Learning Technique

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Jabin T Varughese

Advanced Stock Price Prediction: A Comprehensive Study Using LSTM And GRU Based Machine Learning Technique

Authors: Jabin T Varughese

Unique Paper ID: 183530
Volume: 12
Issue: 3
PageNo: 1782-1791

Keywords: Stock Market Prediction LSTM GRU Hybrid Model Normalization Multi-Layer Perceptron.

Abstract:
The purpose of this paper is to develop an advanced hybrid stock price prediction model by integrating the advantages and benefits of Long Short-Term Memory Model (LSTM) and Gated Recurrent Units (GRU) to facilitate the users in stock market, papers aim is to create an integrated one step solution for stock market prediction. LSTM is highly recommended to capture long-term dependent trends in sequential historical price of a stock whereas GRU handles short-term dependencies and effective in smaller datasets. This paper tries to combine these two models and make a hybrid model for better accuracy and reliability. This hybrid model improves the prediction capability and addresses the limitation which occurs in traditional methods.

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ISSN: 2349-6002
Volume: 12
Issue: 3
PageNo: 1782-1791

Advanced Stock Price Prediction: A Comprehensive Study Using LSTM And GRU Based Machine Learning Technique

Available:https://ijirt.org/article?manuscript=183530

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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