Text Analysis for Prediction of Bitcoin Price by Sequence Neural Network Model

論文翻譯標題: 時序式神經網路的文本分析應用於比特幣價格預測
  • 林 宇德

學生論文: Master's Thesis

摘要

With the accelerated development of artificial intelligence some people want to use it to predict market trends Simultaneously digital currency headed by Bitcoin and Ethereum caught people’s attention because of its soaring price in last year The reputation of digital currency get higher and higher in social media and traditional media People certainly hope to use AI to predict the digital currency market In this research we use Twitter posts as training data and vectored method to represent the tweet information (day vector) per day After cleaning Twitter raw data we converted the tweets in the giving day as day vector and feed the day vector to sequence to Sequence model use to predict the change of Bitcoin price The entire system uses attention model in day vector model and the sequence to sequence model respectively The experiments show that the prediction accuracy rise slightly by increasing day vector dimension and the attention model of the SequenceDecoder model can significantly improve the accuracy Finally we analyzed the 7-day predicted results individually and found that the accuracy decrease when predicting latter day This meet our understanding that it is harder to predict the latter day than the near day
獎項日期2018 八月 9
原文English
監督員Sheng-Tzong Cheng (Supervisor)

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