BEIJING, Feb. 15,
2024 /PRNewswire/ -- WiMi Hologram Cloud Inc.
(NASDAQ: WIMI) ("WiMi" or the "Company"), a leading global Hologram
Augmented Reality ("AR") Technology provider, today announced that
a technology based on the K-Means algorithm has recently been
developed to improve the security and user trust of
bitcoin trading platforms. The technology, based on
the best set of features from real recorded data, identifies
potentially fraudulent users by performing an in-depth analysis of
user behavior on Bitcoin exchange websites, with a
special focus on key metrics.
The K-Means algorithm is an unsupervised learning clustering
algorithm that effectively identifies anomalous users by grouping
them by the similarity of their features. Some users show
significantly different patterns of transaction behavior than
others, making the use of the K-Means clustering algorithm ideal
for solving this problem.
Unlike traditional supervised learning methods, WiMi's K-Means
algorithm for identifying fraudulent users on the
Bitcoin trading platform learns and classifies without
the need for pre-labeled data, making it perform much better when
dealing with large-scale data. The technology not only efficiently
identifies fraudulent users, but also automatically adjusts the
model to respond to those changing fraud tactics,
further improving the security of the trading platform. The main
steps of the technology include:
Data collection and preparation: First of all, the data model
collects a large amount of transaction data, including the number
of transactions, transaction amount, transaction frequency, etc.
These data will be used as input for the K-Means algorithm.
Feature selection: Among the collected data, the most
representative features are selected, and these features will be
used to determine whether the user has fraudulent behavior.
Data pre-processing: Pre-processing the collected data including
operations such as handling missing values, outliers and
normalization to ensure data quality and consistency. This helps to
improve the stability and accuracy of the K-Means algorithm.
K-Means algorithm: The pre-processed data is fed into the
K-Means clustering algorithm. This algorithm divides the users in
the dataset into K clusters, making the users within each cluster
more similar and the users between different clusters less
similar.
Abnormal user identification: The clustering results of the
K-Means algorithm are analyzed to identify the clusters where users
with abnormal behavior are located. These users may exhibit
transaction patterns that are significantly different from other
users, and thus are considered as potentially fraudulent users.
Model evaluation and tuning: The performance of the algorithm is
evaluated. Based on the evaluation results, the algorithm is
adjusted, which may require re-selecting features, adjusting
K-values, etc., to improve the accuracy of the algorithm.
Real-time monitoring and application: The trained K-Means model
is deployed to the Bitcoin trading platform to monitor
users' transaction behavior. When new transaction data is
generated, the algorithm will quickly identify potentially
fraudulent users and take appropriate security measures, such as
sending alerts and freezing accounts.
Feedback: Continuously collect and integrate new data and update
the model to adapt to the ever-changing means of
fraud. Establishing an effective feedback mechanism
enables the system to continuously learn and optimize to improve
its ability to identify new types of fraud.
Through the above steps, the technology can realize accurate
identification and timely response to fraudulent users on
Bitcoin trading platforms, providing users with a more
secure and reliable trading environment. The application prospect
of this technology is to improve the security of the
Bitcoin virtual currency trading platform, and
effectively identify and prevent fraudulent behavior, thus
enhancing user trust and the sustainable development of the
platform. Through the application of the K-Means algorithm,
Bitcoin trading platforms can identify potential
fraudulent users in real-time. This will enable the platform to
quickly take preventive measures to stop fraudulent behavior.
WiMi's K-Means Algorithm for identifying fraudulent users on
Bitcoin trading platforms through in-depth analysis of
user behavior, platforms can obtain more information about users
and understand their trading habits, preferences, and behavioral
patterns. This data helps platforms optimize operational strategies
and provide more personalized services to better meet user
needs.
By establishing an effective feedback mechanism and regularly
updating the model, the platform can continuously improve the
technology, respond to new types of fraudulent behavior promptly,
and maintain a high degree of vigilance against security risks.
WiMi's K-Means algorithm technology is not only able to identify
potential fraud, and improve the security of the
platform and user trust, but also has a great competitive advantage
in the market. By continuously optimizing the algorithm and
fulfilling regulatory compliance requirements, the enterprise has
injected a healthier and more credible development momentum into
the digital currency market. This innovation marks a solid step
towards a more secure and efficient future for digital currency
trading platforms.
About WIMI Hologram Cloud
WIMI 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 Statements
This 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.
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SOURCE WiMi Hologram Cloud Inc.