Examples of using Optimization problems in English and their translations into Chinese
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Many other optimization problems can also be expressed in a least squares form, either minimizing energy or maximizing entropy.
Evolutionary learning applies evolutionary algorithms to address optimization problems in machine learning, and has yielded encouraging outcomes in many applications.
Cooperative co-evolution has been introduced into evolutionary algorithms with the aim of solving increasingly complex optimization problems through a divide-and-conquer paradigm.
Excel Homework Help Microsoft Excel is widely used for simple calculations, data management, daily office tasks or difficult optimization problems.
By mathematically modeling the energy saving processes that occur in nature, scientists have created algorithms that can be used to solve optimization problems in engineering.
In theory, the idea of co-adapted subcomponents is desirable for solving large-scale optimization problems.
Microsoft Excel is widely used for simple calculations, data management, daily office tasks or difficult optimization problems.
Once computers are equipped with semantics, they will be capable of solving complex semantical optimization problems.
Quantum computing particularly helps in solving complex optimization problems such as portfolio risk optimization and fraud detection.
Deep Learning, to a large extent, is really about solving massive nasty optimization problems.
Solve your business problems with a single platform that is designed to handle simple descriptive analysis all the way to the most complex optimization problems.
In mathematics, linear programming(LP) problems are optimization problems in which the objective function and the constraints are all linear.
Through approximation and linearization, many engineering problems can finally be converted into European-style optimization problems.
The most famous kind of network that operates based on stochastic computation is the so-called“Boltzmann” machine, which can solve difficult combinatorial optimization problems.
In mathematics, linear programming problems are optimization problems in which the objective function and the constraints are all linear.
Researchers have been trying to build special-purpose machines to solve optimization problems for years.
So we can use it to solve some optimization problems: those having one or several equality constraints.
Deep Learning, to a large extent, is really about solving massive nasty optimization problems.
Solving large-scale optimization problems often starts with graph partitioning, which means partitioning the vertices of the graph into clusters to be processed on different machines.
How to solve optimization problems.