COMPARING DEEP LEARNING MODELS AND TRADITIONAL MODEL IN ECONOMIC FORECASTING

Baxodir Mo‘minov; Diyora Absalamova

Авторы

Baxodir Mo‘minov Tashkent State University of Economics
Diyora Absalamova Tashkent State University of Economics

Ключевые слова:

Deep Learning, economic forecasting, time series forecasting, RNNs, LSTMs

Аннотация

In the ever-evolving landscape of economic analysis and prediction, the integration of cutting-edge technologies is reshaping the way we perceive and forecast economic trends. Among these transformative technologies, deep learning (DL) stands out as a powerful tool with the potential to revolutionize economic forecasting. In this article, we embark on an exploration of the fundamental concepts surrounding the integration of deep learning into economic forecasting, understanding how this synergy may redefine the accuracy and efficiency of predicting economic outcomes.

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