Abstract
This study focuses on enhancing the performance of Stacked Gated Recurrent Unit (GRU) model in time series data processing, specifically in stock price prediction. The most significant innovation occurs in the integration of a Greedy Algorithm for optimizing hyperparameters such as look-back period, number of epochs, batch size, and units in each GRU layer. Historical stock data from Apple Inc. is utilized for the model's application, emphasizing the model's effectiveness in predicting stock prices. The study methodology involves a sequence of steps, such as data loading, preprocessing, dataset splitting, model construction and evaluation. The role of the Greedy Algorithm's focuses in iteratively adjusting hyperparameters to minimize the Root Mean Squared Error (RMSE) metric, resulting in refining the model's predictive accuracy. The outcomes reveal that the integrated Greedy Algorithm significantly enhances the model's accuracy in predicting stock prices, indicating its potential application in various scenarios requiring precise time series forecasting.
Keywords
References
I (we), the author(s), hereby declare under full moral, financial and criminal liability that the manuscript submitted for publication to the Journal of Computer and Forensic Sciences
a) is the result of my (our) own original research and that I (we) hold the right to publish it;
b) does not infringe any copyright or other third-party proprietary rights;
c) complies with the Journal’s research and publishing ethics standards;
d) has not been published elsewhere, under this or any other title;
e) is not under consideration by another publication, under this or any other title.
I (we) also declare under full moral, financial and criminal liability:
f) that all conflicts of interest that may directly or potentially influence or impart bias on the work have been disclosed in the manuscript;
g) that if the article has been accepted for publishing I (we) will transfer all copyright ownership of the manuscript to the University of Criminal Investigation and Police Studies in Belgrade.
Signed by the Corresponding Author on behalf of the all other authors.