Exemplos de uso de Evolutionary algorithm em Inglês e suas traduções para o Português
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The heuristic method is based on a multi-objective evolutionary algorithm.
Used an evolutionary algorithm based on the particle swarm optimization.
Energy restoration in distribution systems by evolutionary algorithm associated with….
With AI(evolutionary algorithm for example), this can be sped up and leads to interesting setups.
The central fluxes in the obtained global solution are similar to those ones obtained by an evolutionary algorithm.
With this value, the evolutionary algorithm decides what test cases go through and which ones are not interesting any more.
The use of AI in testing takes shape in many different ways,like the use of an evolutionary algorithm or machine learning.
I have formulated an interactive evolutionary algorithm, designed to determine the Harley's initial escape route and subsequent destination.
He had no concept of the idea of an algorithm, but that's what he described in that book, andthis is what we now know as the evolutionary algorithm.
A good example for generating test cases can be the use of an evolutionary algorithm in testing automated parking on a car.
The developed evolutionary algorithm uses commercial models of the network components, provided by the manufacturers in spice file format.
To assist this process of generation of the frb, several techniques can be used andamong them stand out the search technique called evolutionary algorithm ea.
More specifically, we propose an evolutionary algorithm(ea) to automatically evolve bayesian network classifiers bncs.
The video tutorials take a collection of data points from a swinging pendulum over time andthen have the Eureqa software determine the function that best explains its wave using an evolutionary algorithm.
On the Strength Pareto Evolutionary Algorithm SPEA, proposed by, is used the selection based on the dominance relation to evaluate and select the solutions.
The present work hasas main goal to study and also to apply a recent proposed evolutionary algorithm called Migrating Birds Optimization(MBO) for CNN parameter optimization.
Based on the constructal principle,it¿s proposed an evolutionary algorithm that builds a cavity able to maximize the heat transfer between solid body and ambient.
An evolutionary algorithm called sce-ua(shuffled complex evolution- university of arizona), which looks for optimize parameters of control flow curves generation, is used. these curves may be modeled by nurbs non-uniform.
This approach is compared in this work with the traditional mono-objective evolutionary algorithm(ga), classical algorithms(pls and spa) and another classic multi-objective algorithm nsga-ii.
In this paper a new evolutionary algorithm(ea), the backtracking search optimization algorithm(bsa), is adapted for solving optimization problems with restrictions, and with continuous and discrete design variables.
The fitness function was determined through a statisticalevaluation method(difference of means), thus enabling the comparison of how different options of fitness functions could impact the performance of the proposed parallel multi-objective evolutionary algorithm.
The methodology is based on multiobjective evolutionary algorithm in tables, initially developed for the service restoration problems in distribution systems.
Their results showed the both techniques reached closed solutions and are capable of avoiding local optimum. proposed a Genetic Algorithm with a new way to select the most adapted population and a new mutation operator, based on probabilities distribution.used a multi-objective evolutionary algorithm CMOEA.
This work proposes the use of multi-objective evolutionary algorithm on tables(aemt) for variable selection in classification problems, using linear discriminant analysis.
The evolutionary algorithm with binary-real quantum inspiration aeiq-br is used in neve to automatically generate new classifiers for the ensemble, determining the most appropriate topology for the new network and by selecting the most appropriate input variables and determining all the weights of the neural network.
To achieve this,our tuning mechanism is inspired by two key ideas:(1) an evolutionary algorithm to generate and test new job configurations, and(2) data sampling to reduce the cost of the tuning process.
In this thesis the evolutionary algorithm named differential evolution(de) is compared to other derived algorithms and also other evolutionary algorithms based on population.
This dissertation intends to provide the reader with an inner simulation of daniel dennetts form of reasoning, spreading over his whole philosophy,emphasizing his treatment of patterns, the evolutionary algorithm, consciousness, and his use of illata, abstracta, semantic, and synthax, to carve nature at its joints, especially biology and the human mind.
In this thesis, we introduce a new evolutionary algorithm for induction of regression trees, including multiple strategies in its evolutionary cycle for dealing with missing data.