A Comparative Analysis of Long Short-Term Memory Networks and Artificial Neural Networks for Gold Price prediction

Abstract

We have come up with an extra simple approach to sum up your research's objectives and results We looked into gold price prediction, which is a continually sought- after investment option. For this aim, our research compared various methods. We took use of temporal trends in the gold price data by using LSTM networks. Furthermore, we examined how well Artificial Neural Networks (ANN) predicted actual gold prices. By combining ANN, our unique method maximizes the benefits of both models. ANN has become a powerful technique for capturing intricate relationships in data, which is noteworthy. According to this research, hybrid models such as ours can improve the prediction of gold prices, assisting with risk management and investment choices. As the price of gold fluctuate frequently, more people are choosing to invest in gold. However, investing in gold may become riskier due to the unpredictability of these price fluctuations. This is where "Gold Price Prediction" enters the picture; its main goal is to predict future gold prices by utilizing various machine learning approaches.