Examples of using Genetic algorithms in English and their translations into Indonesian
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Using Genetic Algorithms.
Local search optimization techniques(e.g., genetic algorithms).
Genetic Algorithms and Their Appi.
Neural networks, genetic algorithms and more….
Genetic algorithms and their applications.
Applying the"X" and"L" genetic algorithms to the ATS-3200.
Genetic Algorithms are based on Darwin's Theory of Evolution.
He was talking about genetic algorithms, quantum teleportation.
Genetic Algorithms are inspired by the theory of evolution.
To solve this problem, they used Genetic Algorithms.
Genetic algorithms are a type of evolutionary algorithm. .
And we're learning from neural nets, genetic algorithms, evolutionary computing.
Genetic algorithms in particular became popular through the writing of John Holland.
An alternative approach would be to use genetic algorithms and methods from classical AI.
Among these, Genetic Algorithms are most popular and have been successfully applied to various optimization problems.
The most commonly used techniques in stock market prediction include genetic algorithms(GA) and artificial neural networks(ANNs).
You're working with genetic algorithms and other means to actually breed better machines.
These terminologies denote the field of evolutionary computing and consider evolutionary programming,evolution strategies, genetic algorithms, and genetic programming as sub-areas.
In genetic algorithms, in some cases a mutation will increase the fitness of the offspring, in other cases, it will reduce it.
The IX Series is unique in the industry for using EITPL“Genetic Algorithms”(GA) in its image processing technology.
Investment brokers use Genetic Algorithms to create the best possible combination of investment opportunities for their clients.
The Strategy Tester with support for visual testing, optimization, genetic algorithms, a distributed network of testing agents, and much more.
Genetic algorithms, evolutionary strategies and genetic programming repre- sent rapidly growing areas of AI, and have great potential.
The NASA Advanced Supercomputing facility(NAS) ran genetic algorithms using the Condor cycle scavenger running on about 350 Sun Microsystems and SGI workstations.
Genetic algorithms depend on the input parameters, they are the number of population, the probability of crossover, mutation probability and the number of generations.
And evolutionary algorithms, or genetic algorithms that mimic biological evolution, are one promising approach to making machines generate original and valuable artistic outcomes.
Genetic algorithms: Optimization techniques that use process such as genetic combination, mutation, and natural selection in a design based on the concepts of natural evolution.
Genetic algorithms find application in bioinformatics, phylogenetics, computational science, engineering, economics, chemistry, manufacturing, mathematics, physics and other fields.