3. Bitcoin is a digital currency (also called
crypto-currency) that is not backed by any
country's central bank or government. Bit
coins can be traded for goods or services
with vendors who accept Bit coins as
payment.
Bitcoin-to-Bitcoin transactions are made by
digitally exchanging anonymous, heavily
encrypted hash codes across a peer-to-peer
network.
4.
5. Blocks are added to the chain in the process
of mining Bitcoins. The process of mining
revolves around solving complex
computational puzzles, and the incentive for
miners to participate are transaction fees and
Bitcoin rewards. To solve these puzzles,
miners need computational power, which is
measured by the Hashrate.
6.
7.
8. Since its invention, Bitcoin has gained amazing
popularity and much attention in various
research fields, including computer science,
economics and cryptography. With the
emergence of the Blockchain technology, the
innovative ledger technology underpinning
Bitcoin.
This study employs Bayesian neural networks
(BNN) to model and predict the short-term
Bitcoin prices. Some most relevant factors like
Blockchain information, macroeconomic factors
and foreign exchange rates are selected as input
features to improve the forecasting accuracy of
proposed model.
9. Unlike existing fiat currencies with central
banks, Bitcoin aims to achieve complete
decentralization. Participants in the Bitcoin
market build trust relationships through the
formation of Blockchain based on
cryptography techniques using hash
functions. Inherent characteristics of Bitcoin
derived from Blockchain technologies have
led to diverse research interests not only in
the field of economics but also in
cryptography and machine learning.
10. 1. In the author explains how the cost of mediation
increases the transation cost and how it limits the
minimum practical transation size. The author also
lays emphasis on the need for an electronic payment
system based on cryptographic proof instead of trust
and allowing any two willing parties to transact
directly with each other without the need for a
trusted third party.
2. In the book the author discusses techniques such as
least squares method which helps in performing
mathematical regression analysis that finds the line
of best fit for the dataset. This also provides a visual
demonstration of the relationship between the data
points.
11. 3. In the author has introduced a wide variety of
models to perform data analysis. As the dataset
consists of various factors contributing to change
in one attribute over a period of time, we find it
best to choose linear and multiple regression for
data analysis.
4. In the author has mentioned the two approaches
to predicting price development, this dataset
provides information only for technical analysis
as fundamental analysis examines the underlying
forces of the economy.
12. Time series analysis, nonlinear methods, such as
kernel regression model, exponential autoregressive
models, artificial neural network (ANN), BNN, and
support vector regression, have attracted research
interest and exhibited improved predictive
performance for various time series data .
Bayesian neural networks (BNN) is a transformed
Multilayer perceptron (MLP) which is a general term
for ANNs in the fields of machine learning. The
networks have been successful in many application
such as image recognition, pattern recognition,
natural language processing, and financial time series
also it solves overfitting problem.
13. Average block size (MB): the size of a block verified by all
participants
Transactions per block: average number of transactions per
block.
Median confirmation time: the median time for each transaction
to be accepted into a mined block and recorded to the ledger.
Hash rate: estimated number of Tera (trillion) hashes per a
second all miners (market participants to solve a hash problem
for making a block) is performing.
Difficulty: next difficulty =(previous difficulty ∗2016 ∗ 10
minutes)/(time to mine last 2016 blocks)
Cost % of a transaction: miners’ revenue as the percentage of the
transaction volume.
Miners revenue: Total value of coin-base block rewards and
transaction fees paid to miners.
Confirmed transaction:
Total number of a unique Bitcoin:
14. Historical Transaction data of the bit coin which
is representing the Rate of the bit coin that
include, how they are changing and what are the
parameters that are going to affect the rate of
the bit coin. Price, value and timing are few
parameters which affect bit coin. The change of
data every second depends on the mining rate
and the demand of the bit coin. So, who so ever
is the person who gives the transaction fee for
the completion of their transaction should be
completed on average 8-10 minutes and the rest
who has not given the transaction fee there
transaction will not be completed and will come
under transaction pool.
15. We have the Data Sets and we will be applying
the concept of machine learning. Different
techniques of machine learning like KNN (K
Nearest Neighbor), Naive based and decision tree
can be applied and the one which will give more
accurate and précised result will be used further
for the prediction model in the Deep Learning
concept for the making of the neural networks
that will help in the prediction .So by this we can
predict the price of the bit coin in the coming
years depending on the consumption, demand
and supply of the bit coins.
