Examples of using Evolutionary algorithms in English and their translations into Slovak
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Medicine
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Computer
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Programming
Evolutionary Algorithms(EAs).
Genetic and evolutionary algorithms.
Evolutionary algorithms in intelligent control.
Neural networks, and evolutionary algorithms.
Evolutionary algorithms(allowance 3/0).
There are three basic types of evolutionary algorithms.
Evolutionary algorithms, neural networks, fuzzy logic.
Neural networks, evolutionary algorithms, fuzzy systems.
It is also the principle of genetic or evolutionary algorithms.
Parallel evolutionary algorithms.
Charles Ofria, a computer scientist at Michigan State University, who was involved with the research, says it may helpcomputer programmers make more efficient evolutionary algorithms.
That's where genetic and evolutionary algorithms come in.
Inspired by the biological concept and usefulness of genotypes,computer science employs simulated genotypes in genetic programming and evolutionary algorithms.
Xuewei Qi and a team of UCRresearchers are using vehicle connectivity and evolutionary algorithms to improve the efficiency of Plug-In Hybrid Electric Vehicles.
One fun subject was Evolutionary algorithms, once the problem was pseudo solved I spend quite some time just playing with the solution, and how to converge towards it faster, yet still precise enough.
The highly efficient EMS developed and simulated byQi and his team combines vehicle connectivity information(such as cellular networks and crowdsourcing platforms) and evolutionary algorithms- a mathematical way to describe natural phenomena such as evolution, insect swarming and bird flocking.
Using an evolutionary algorithm, patterns were optimized for their capacity to precisely control the paths of the filaments.
The robots, which are lessthan 1mm long, are designed by an“evolutionary algorithm” that runs on a supercomputer.
And we're learning from neural nets, genetic algorithms, evolutionary computing.
In a group with so many IT people, I do have to mention what I'm not going to talk about, and that is that your field is one that has learned an enormous amount from living things, on the software side. So there's computers that protect themselves, like an immune system, and we're learning from gene regulation and biological development. And we're learning from neural nets,genetic algorithms, evolutionary computing.