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Knowledge Discovery and Cryptocurrency Price Prediction Based on Blockchain Framework

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Abstract
separated from the other layer to give the access to developers to replace or add a new module
without any effect on the rest of the system. Moreover, the general service architecture contains
the sequence diagram and flowchart. The service architecture is mapped into two distinct
architectures, i.e., knowledge discovery and blockchain framework.
The knowledge discovery architecture aims to provide detailed information about internet
users' shared content related to cryptocurrency. Similarly, the designed platform contributes to
the topic modeling approach by using Latent Dirichlet Allocation (LDA) to generate the concept
of shared information in different categories and using the prediction and optimization
approaches to create the cryptocurrency's future price in terms of allowing the user for selecting
the correct option which meets the defined requirement form user.
The blockchain architecture aims to provide a secure and transparent platform for the
transactional process between networks. Regarding the defined rules and smart contracts in the
system, the process has a visible path to follow the transactions through the network. The
outcomes of this study revealed that the proposed model is efficient due to fault-tolerant,
scalable, and provides flexibility for the new business models.
Author(s)
샤흐버지 제이납
Issued Date
2022
Awarded Date
2022-08
Type
Dissertation
URI
https://dcoll.jejunu.ac.kr/common/orgView/000000010895
Affiliation
제주대학교 대학원
Department
대학원 컴퓨터공학과
Advisor
Byun, Yung-cheol
Table Of Contents
Abstract 1
Chapter 1: Introduction 3
1.1 Motivation. 3
1.2 Background. 4
1.3 Problem Statement. 5
1.4 Research Goal. 7
Chapter 2: Related Work 9
2.1. Concept of Cryptocurrency. 9
2.2. Concept of Knowledge Discovery for Cryptocurrency Technology 11
2.2.1 Topic Modeling 16
2.2.2 Topic Discovery 18
2.2.3 Information Analysis System 21
2.3. Concept of Cryptocurrency in Blockchain 23
2.4. Arts and Regulations of Financial Statements 24
Chapter 3: Proposed Cryptocurrency Price Prediction 31
3.1 Cryptocurrency Prediction Architecture 31
3.1.1 Data Acquisition for Cryptocurrency 33
3.1.2 System Process 37
3.1.3 Control and Optimization 37
3.2 Topic Modeling Based on LDA in Cryptocurrency Dataset. 37
3.2.1 Data pre-processing 39
3.3 General Cryptocurrency Prediction Architecture based on System Security 42
3.3.1 Service Layer 44
3.3.2 Predictive Optimal Control Layer 44
3.3.3 Blockchain Layer 45
3.3.4 Physical Layer 46
3.4 Cryptocurrency Prediction Architecture based on Blockchain 47
3.4.1 Difficulty of Mining, Profitability and Hashrate 50
3.4.2 Confirmation Time and Market Capitalization 50
3.5 Cryptocurrency Predictive Analysis . 51
3.5.1 Reinforcement Learning Prediction 53
3.5.2 Price Prediction 56
3.5.3 Risk Management 57
Chapter 4: Development of Cryptocurrency Prediction 59
4.1 Design of Cryptocurrency Prediction Framework 59
4.1.1 Cryptocurrency knowledge Discovery Framework 61
4.1.2 Cryptocurrency Blockchain Framework 63
4.2 Implementation of Cryptocurrency Predictive Analysis. 64
4.2.1 Development Environment of Cryptocurrency Predictive Analysis 64
4.2.2 Experimental Setup of Cryptocurrency Prediction 66
4.2.3 Experimental Results of Cryptocurrency Prediction 70
4.3 Performance Analysis of Cryptocurrency Prediction . 86
4.3.1 Price Management for Prediction 86
4.3.2 Risk Management for Prediction 89
4.3.3 Evaluation Metrix of the Cryptocurrency Prediction 97
Chapter 5: Conclusion and Future Directions 101
References 103
Degree
Doctor
Publisher
제주대학교 대학원
Appears in Collections:
General Graduate School > Computer Engineering
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