BEIJING, Sept. 22,
2023 /PRNewswire/ -- MicroAlgo Inc. (NASDAQ:
MLGO) (the "Company" or "MicroAlgo"), today announced that a
knowledge-enhanced backtracking search algorithm was developed,
while the research and development of evolutionary computational
methods provided the technical basis for the emergence of the
MicroAlgo's knowledge-enhanced backtracking search algorithm. The
algorithm aims to improve the efficiency, accuracy and adaptability
of problem-solving and provide more possibilities for optimization
and decision support for enterprises and research institutions. The
development and application of the algorithm is expected to have a
significant impact in various fields.
Knowledge-enhanced backtracking search algorithm combines
backtracking search strategy and knowledge learning to improve the
performance and efficiency of the algorithm. The basis of the
Knowledge-enhanced backtracking search algorithm is backtracking
search. Backtracking search is an iterative optimization method
that starts with one possible solution and then searches for an
optimal or near-optimal solution to the problem by progressively
adjusting and improving the current solution. At each step, the
algorithm tries different alternatives and then evaluates the
quality of those alternatives and decides on the next move.
MicroAlgo Inc.'s knowledge-enhanced backtracking search
algorithm introduces adaptive control parameters to enable dynamic
adjustment of the search step size. The values of these parameters
are automatically adjusted based on global and local information
about the population in the current iteration. This means that the
algorithm is able to flexibly adjust the depth and breadth of the
search according to the characteristics of the problem and the
progress of the search. This helps to balance the exploration and
exploitation capabilities of the algorithm, thus improving search
efficiency.
Knowledge-enhanced backtracking search algorithm uses different
mutation strategies which are guided by various information. These
strategies guide the algorithm to generate new solutions based on
prior search experience and domain knowledge. The goal of these
strategies is to increase the diversity of the search, help the
algorithm to jump out of the local optimal solution and improve the
efficiency of the global search. The selection and adaptation of
mutation strategies can be based on the nature and needs of the
problem.
To further improve the performance of the algorithm, the
knowledge-enhanced backtracking search algorithm introduces
multiple population strategies. This means that the algorithm can
process multiple populations simultaneously and operate in
different search regions. Each population can use different
parameter settings and search strategies to increase the efficiency
of the global search. The multiple population strategy helps the
algorithm to better explore the solution space and find better
solutions.
The core of MicroAlgo Inc.'s knowledge-enhanced backtracking
search algorithm lies in the knowledge-learning mechanism. At each
iteration of the algorithm, it accumulates and updates knowledge
about the problem. This knowledge include solutions that have been
tried, their quality assessments, and information about the
structure of the problem. Through knowledge learning, the algorithm
is able to converge to better solutions faster because it utilizes
the experience of previous searches.
Key points of the technical logic and principles: First, the
algorithm initializes the initial solution and sets the initial
values of the control parameters. Then in each iteration, the
algorithm selects a candidate solution or generates a new solution
and evaluates its quality. Among other things, the adaptive control
parameters are adjusted based on global and local information to
determine the depth and breadth of the search in the next step.
Second, the mutation strategy guides the generation of new
solutions based on knowledge to increase search diversity. The
multi-population strategy allows running multiple populations in
parallel to increase the global search efficiency. Finally, the
knowledge learning mechanism updates the algorithm's knowledge base
with attempted solutions and their evaluations.
The algorithm optimizes the search process of the problem in a
highly flexible and intelligent way by means of adaptive control
parameters, novel mutation strategies, multi-population strategies,
and knowledge-learning mechanisms, thus improving the performance
and efficiency of the algorithm. This makes it a powerful tool for
dealing with complex optimization problems and decision
support.
MicroAlgo Inc.'s knowledge-enhanced backtracking search
algorithm is an innovative technology with a vast potential for
future development. Knowledge-enhanced backtracking search
algorithms will be used in more industries, including healthcare,
energy, transportation, retail, and more. Problems and challenges
in different industries will drive the algorithms to evolve and
improve. With the continuous progress of the technology and the
practical application of the algorithms, we can expect the
continuous optimization of the knowledge-enhanced backtracking
search algorithms, including more efficient search strategies, more
flexible knowledge-learning mechanisms, and more powerful
multi-group strategies.
In the future, the algorithm may be extended to handle
multi-modal problems where there are multiple local optimal
solutions. This will involve more complex search spaces and
finer-grained strategies. MicroAlgo Inc.'s knowledge-enhanced
backtracking search algorithm may be integrated with machine
learning and deep learning methods to handle large-scale data and
complex problems. This integration could provide more powerful
problem-solving capabilities. Further development of algorithms may
lead to the emergence of automated decision-support systems that
can provide real-time optimization recommendations and decision
support to businesses and organizations based on information from
real-time data and knowledge bases.
The knowledge-enhanced backtracking search algorithm represents
a promising technology that can open up new possibilities for
optimization problem-solving and decision making in the enterprise.
Through continuous research and innovation, we can expect to see a
wider range of applications and more efficient performance of this
algorithm in various domains. It will become a key driver of
technological innovation for enterprises, bringing more
opportunities and competitive advantages for future
development.
About MicroAlgo Inc.
MicroAlgo Inc. (the "MicroAlgo"), a Cayman
Islands exempted company, is dedicated to the development and
application of bespoke central processing algorithms. MicroAlgo
provides comprehensive solutions to customers by integrating
central processing algorithms with software or hardware, or both,
thereby helping them to increase the number of customers, improve
end-user satisfaction, achieve direct cost savings, reduce power
consumption, and achieve technical goals. The range of
MicroAlgo's services includes algorithm optimization,
accelerating computing power without the need for hardware
upgrades, lightweight data processing, and data intelligence
services. MicroAlgo's ability to efficiently deliver software and
hardware optimization to customers through bespoke central
processing algorithms serves as a driving force for MicroAlgo's
long-term development.
Forward-Looking Statements
This press release contains statements that may constitute
"forward-looking statements." Forward-looking statements are
subject to numerous conditions, many of which are beyond the
control of MicroAlgo, including those set forth in the Risk Factors
section of MicroAlgo's periodic reports on
Forms 10-K and 8-K filed with the SEC. Copies are
available on the SEC's website, www.sec.gov. Words such as
"expect," "estimate," "project," "budget," "forecast,"
"anticipate," "intend," "plan," "may," "will," "could," "should,"
"believes," "predicts," "potential," "continue," and similar
expressions are intended to identify such forward-looking
statements. These forward-looking statements include, without
limitation, MicroAlgo's expectations with respect to future
performance and anticipated financial impacts of the business
transaction.
MicroAlgo undertakes no obligation to update these statements
for revisions or changes after the date of this release, except as
may be required by law.
View original
content:https://www.prnewswire.com/news-releases/microalgo-inc-announced-knowledge-enhanced-backtracking-search-algorithm-301936054.html
SOURCE MicroAlgo Inc.