An AI-Based Minimax Optimization Approach for Cryptocurrency Price Prediction and Fraud Detection
Keywords:
Artificial Intelligence, RNN, CNN, Cryptocurrency, Volatility, Price Predictor, Fraud Detection, LSTM, Google Colab, Sustainability.Abstract
This paper explores the integration of AI (artificial intelligence) in predicting the volatility of the crypto space and detecting fraudulent activities by adopting the quantitative approach to examine fraud detection by using a CNN model and the ability to predict price volatility by using LSTM networks with the help of Google Colab. The findings of this study highlight that artificial intelligence is a critical enabler of long term stability and trust in the evolving crypto-space. The originality of this study lies in its investigation of the sustainable role of artificial intelligence in predicting future prices and detecting fraudulent activities simultaneously, and integrating efficiency, accuracy, and long-term applicability, which has been explored to a limited extent. Therefore, further research in other related sectors should be explored to understand the influence of artificial intelligence in Crypto-space. This study offers useful insights for regulators, policymakers, and portfolio managers and offers scope for further research. However, the study adopted secondary data for this research, which limits the research and its ability to capture the dynamic nature of cryptocurrency market.
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