WiMi Hologram Cloud Inc. (NASDAQ: WIMI) ("WiMi" or the "Company"),
a leading global Hologram Augmented Reality ("AR") Technology
provider, today announced an LSTM-based data analysis system to
provide clients with cutting-edge tools to trade in the complex
cryptocurrency environment.
As a decentralized digital currency, the price
of Bitcoin is affected by a variety of factors, such as market
demands, policy regulations, and technological innovations.
Therefore, the prediction of price trends needs to comprehensively
consider these factors and find patterns from a large amount of
data. Traditional data analysis methods make it difficult to handle
such complex data, but the LSTM algorithm can solve this
problem.
WiMi uses the LSTM algorithm (a machine learning
algorithm) to predict cryptocurrency prices, which allows it to
more accurately predict the price of Bitcoin. The LSTM algorithm is
a recurrent neural network. The system uses a variety of data
sources, including historical prices, transaction volumes, social
media data, and more. The system uses the LSTM algorithm to analyze
these data and generate predictions of bitcoin price trends. LSTM
is a special type of RNN architecture that can efficiently handle
time-series-dependent data. It avoids the problem of gradient
vanishing or gradient explosion when dealing with long-term
dependencies by introducing a "gate" structure to control the flow
of information. This makes LSTM widely used in the fields of speech
recognition, natural language processing, and time series
analysis.
Cryptocurrency price is sequential, with each
piece of data dependent on the one before it. The ability of LSTMs
to process and memorize information over extended sequences allows
them to capture complex patterns that traditional models might
miss. The "long" in LSTM refers to the model's ability to retain
information over a longer period. This is critical in the
cryptocurrency market, and LSTM's long-term memory makes it adept
at recognizing and exploiting these trends. Cryptocurrency markets
are non-linear and dynamic, characterized by sudden and
unpredictable changes. LSTM's ability to model non-linear
relationships allows it to adapt to changing markets. LSTM is adept
at automatically learning and extracting relevant features from
input data. In the context of the predictable price of Bitcoin,
this means that the model can identify and utilize important market
metrics, thus simplifying the development process.
WiMi utilizes the LSTM algorithm to build an
efficient data analysis system that is capable of deep learning
from historical Bitcoin transaction data to extract key factors
that influence price trends. The system mainly includes the
following modules:
Data pre-processing: Processing raw data to
ensure the quality of the data. This includes cleaning the data,
dealing with missing values, and normalizing the data to ensure
that the inputs to the algorithm are consistent and meaningful.
Model architecture: The architecture of the LSTM
model is a critical component of its effectiveness. WiMi leveraged
its expertise in deep learning to design a sophisticated
architecture that balances model complexity, optimizing
prediction accuracy and real-world applicability.
Hyper-parameter tuning: Fine-tuning the
parameters of the LSTM model is critical to achieving optimal
performance. using advanced optimization techniques, WiMi
systematically explores the hyper-parameter space to ensure model
robustness and adaptability to varying market conditions.
Training and validation: Training an LSTM model
requires a large amount of data. WiMi carefully selects the data
and divides it into training and validation sets to avoid
over-fitting. Training the LSTM model with historical data allows
it to learn and model the dynamics of the Bitcoin price.
Prediction and Evaluation: Based on the
extracted features and the trained model, the bitcoin price is
predicted, and the accuracy of the prediction is evaluated through
cross-validation and other methods.
Real-time update and optimization: Based on the
latest market data and feedback, the model is constantly updated
and optimized to ensure the accuracy of the prediction.
Continuous learning: Recognizing the dynamic
nature of the cryptocurrency market, WiMi has implemented a
continuous learning system. This allows the LSTM model to adapt to
changing markets, incorporating new data and enhancing its
predictive capabilities.
WiMi's data analysis system benefits from the
advanced LSTM algorithm, which not only has superior learning and
memory capabilities but also uses deep learning to extract key
factors affecting the price of Bitcoin from complex data, thus
ensuring the high accuracy of the system's predictions. The
system's real-time nature is also a compelling feature, enabling it
to instantly process the latest market data and provide investors
with rapidly generated price trend forecasts, enabling them to make
sharp decisions in a rapidly changing market.
On the other hand, the system demonstrates
excellent scalability, with the ability to flexibly expand in
response to changes in data volume to meet data analysis of
different sizes and needs. This flexibility allows the system to
adapt to the diversity of markets and data distribution, thus
maintaining high prediction accuracy under different environments.
At the same time, the LSTM model can provide investors with more
credible reasons and increase trust in decision-making compared to
traditional black box models.
WiMi's LSTM-based Bitcoin price prediction data
analysis system is important for cryptocurrency and other
industries. Investors and traders can use accurate price
predictions to make informed decisions and minimize the risks
associated with market volatility. WiMi's system enables users to
make strategic decisions using data-driven insights. The LSTM
algorithm makes complex algorithmic trading strategies simple.
Traders can automate buy and sell decisions based on the model's
predictions, capitalizing on market opportunities in real time.
Accurate price predictions help improve market efficiency by
reducing information asymmetry. As more and more people adopt
advanced predictive models, markets are likely to become more
rational and less prone to irrational exuberance or panic
selling.
The cryptocurrency market, and Bitcoin in
particular, provides a dynamic and challenging environment for
traders. By addressing the unique challenges of the cryptocurrency
market and harnessing the power of LSTM, WiMi aims to revolutionize
the way traders take advantage of the opportunities presented by
the volatility of the Bitcoin price. As WiMi continues to break new
ground in technological innovation, their fruition has even
influenced predictive analysis and algorithmic trading.
About WIMI Hologram CloudWIMI Hologram Cloud,
Inc. (NASDAQ:WIMI) is a holographic cloud comprehensive technical
solution provider that focuses on professional areas including
holographic AR automotive HUD software, 3D holographic pulse LiDAR,
head-mounted light field holographic equipment, holographic
semiconductor, holographic cloud software, holographic car
navigation and others. Its services and holographic AR technologies
include holographic AR automotive application, 3D holographic pulse
LiDAR technology, holographic vision semiconductor technology,
holographic software development, holographic AR advertising
technology, holographic AR entertainment technology, holographic
ARSDK payment, interactive holographic communication and other
holographic AR technologies.
Safe Harbor StatementsThis press release
contains "forward-looking statements" within the Private Securities
Litigation Reform Act of 1995. These forward-looking statements can
be identified by terminology such as "will," "expects,"
"anticipates," "future," "intends," "plans," "believes,"
"estimates," and similar statements. Statements that are not
historical facts, including statements about the Company's beliefs
and expectations, are forward-looking statements. Among other
things, the business outlook and quotations from management in this
press release and the Company's strategic and operational plans
contain forward−looking statements. The Company may also make
written or oral forward−looking statements in its periodic reports
to the US Securities and Exchange Commission ("SEC") on Forms 20−F
and 6−K, in its annual report to shareholders, in press releases,
and other written materials, and in oral statements made by its
officers, directors or employees to third parties. Forward-looking
statements involve inherent risks and uncertainties. Several
factors could cause actual results to differ materially from those
contained in any forward−looking statement, including but not
limited to the following: the Company's goals and strategies; the
Company's future business development, financial condition, and
results of operations; the expected growth of the AR holographic
industry; and the Company's expectations regarding demand for and
market acceptance of its products and services.
Further information regarding these and other
risks is included in the Company's annual report on Form 20-F and
the current report on Form 6-K and other documents filed with the
SEC. All information provided in this press release is as of the
date of this press release. The Company does not undertake any
obligation to update any forward-looking statement except as
required under applicable laws.
ContactsWIMI Hologram Cloud Inc.Email:
pr@wimiar.comTEL: 010-53384913
ICR, LLCRobin YangTel: +1 (646) 975-9495Email:
wimi@icrinc.com
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