The development in stock market prediction is represented as a significant role and it received immense interest as predicting stock prices effectively which cause striking profits by creating appropriate decisions. Stock market prediction is the most important confronts on account of non-stationary, blaring, and chaotic data. Hence, prediction turns out to be demanding between investors to invest the money in order to make earnings. At first, to blockchain Network Bridge the blockchain network is subjected from that bitcoin data is obtained which is pursued with the prediction of bitcoin. The developed Raindrop optimization method based on Deep LSTM is used for the prediction of Bitcoin. Initially, based on the Rate of Change Rate (ROCR), Average True Range (ATR), Double Exponential Moving Average (DEMA), Simple Moving Average (SMA), and Moving Average Convergence Divergence (MACD) flow strength indicators are extracted from the blockchain data. On the basis of the extracted features, the prediction is performed exploiting Raindrop optimization algorithm-based Deep LSTM, which is a combination of Raindrop optimization algorithm with Deep LSTM. Subsequently, the Raindrop optimization algorithm is used to determine the optimal weights in Deep LSTM. The simulation of the developed algorithm is done from the explicitly accessible dataset. The examination of technique regarding MAE and RMSE shows that the developed method attained a minimal Mean Absolute Error (MAE) and the minimal Root Mean Squared Error (RMSE) correspondingly.
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