Μελέτη οικονομικών στοιχείων για την πρόβλεψη συμπεριφοράς τους στην σύγχρονη οικονομική πραγματικότητα με χρήση τεχνητών νευρωνικών δικτύων

Κυριακού, Κυριάκος

Master Thesis

Author

Κυριακού, Κυριάκος

Date

2024-05

Abstract

In an era characterized by exponential data growth and the relentless march of technological innovation, artificial neural networks (ANNs) have emerged as a transformative force in the realm of machine learning and artificial intelligence (AI). These flexible computational models, inspired by the complex structure of the human brain, have embarked on an exciting journey from their humble beginnings to become the cornerstone of modern data analysis, pattern recognition and predictive modeling. In this dynamic era where data flows abundantly, solving nonlinear problems has become an absolute necessity, especially in the financial sector. The financial landscape presents myriad challenges, many of which are inherently nonlinear and complex. In this context, artificial neural networks shine as powerful tools for analyzing complex financial information. This research paper explores the application of artificial neural networks to modern economic reality using machine learning techniques and time series prediction. It seeks to uncover the potential of AI as a means of addressing the complex challenges facing the financial sector today. Through a combination of historical context, theoretical foundations, practical application and critical analysis, this thesis aims to contribute to the evolving discourse on the integration of cutting-edge technology in the financial sector. Ultimately, it seeks to make available information that can provide more accurate economic forecasting and data-driven decision making in an era defined by data abundance and technological advances.

Postgraduate Studies Programme

Προηγμένα Συστήματα Πληροφορικής

Department

Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών Συστημάτων

Number of pages

Language

Greek

URI

https://dione.lib.unipi.gr/xmlui/handle/unipi/17416

Collections

Τμήμα Ψηφιακών Συστημάτων

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Except where otherwise noted, this item's license is described as
Αναφορά Δημιουργού-Όχι Παράγωγα Έργα 3.0 Ελλάδα