Developing an Advanced AI-based 24 Carat Gold Price Prediction Model in India Utilizing Long Short-Term Memory (LSTM) Neural Networks with an Accuracy of 96.79%: A Comprehensive Approach to Forecasting Market Trends and Economic Influences

This research explores the application of neural networks to predict gold prices, leveraging machine learning techniques to enhance financial analysis based on historical data.The research involves the development of a predictive model utilizing data normalization, the Adam optimiser, and the mean square error function.The model was trained on historical prices in the last 20 years, achieving an impressively high accuracy of 96.79% in predicting the future price one year ahead.Despite the promising results, the research identified key challenges, such as the model's sensitivity to input data and the inherent complexity of financial markets.These findings emphasize the potential of machine learning in finance, while also highlighting the need for ongoing refinement and the incorporation of broader, more comprehensive datasets to improve the model's precision.This study essentially focuses on the interlacing of machine learning and the world of financial analysis, offering key insights for future research and practical applications in market prediction.