Published Paper Details:

Cryptocurrency is a type of digital money in which histories are kept by a decentralised system employing encryption before centralised expert and financial transactions are confirmed through mining. One of its goals is to provide users and investors more control by decentralising the influence of institutions and organisations. Due to its recent rise in importance, relevance, and influence on people's lives as a result of increasing access, which necessitates systems with strong processors for mining, etc., numerous considerations regarding its adoption have been considered in India. In recent years, Bitcoin has increased in significance as well as in popularity and importance. With significant advancements in this area, many firms around the world have realised how crucial it is to use this technology in order to virtually take advantage of the many numerical benefits. Predictions of stock prices, cryptocurrency prices, and real estate price values and other sectors and domains where it is used In the current financial exchange environment, price prediction is one of the major issues since buyers and sellers of cryptocurrencies face an intriguing conundrum. It appears to have reached previously unheard-of heights in recent years, giving rise to ideas that defend the pattern of its upsurge. Recently, investors, researchers, and other economists have been quite busy trying to figure out if the movements and brief swings of cryptocurrencies can be predicted. In order to enforce these verdicts in the bitcoin market, it is critical to have the most reliable and accurate methods of price prediction, and liability and asset analysis, at least for the near future. We may do this by utilising machine learning models that can recognise long-term dependencies, such as LSTM, RNN etc. Some of the crucial factors used include close price, offered price, low price, high price, market cover and size, as well as relationship between a limited cryptocurrencies. This evaluation is focused on identifying critical factors that influence how unpredictable a transaction is by utilising the system to improve the usability of this practise. It was able to examine ten papers on cryptocurrency and price forecast of commodity that used a variety of methods, including RF, LSTM, ANN, MAPE, and MBE In conclusion, these research have demonstrated an optimally high level of estimating accuracy. In order to be able to accurately estimate the prices, a variety of methodologies and algorithms were used, and these varied significantly amongst the articles. While the majority viewed the issue from a different perspective, a small group continued to work on the conclusions of earlier approaches by adding newer layers. The numerous methods and tactics that our group discussed all seemed to have advantages and disadvantages of their own while being appropriate for particular situations.