genetic algorithms
Using Genetic Algorithms in Secured Business Intelligence Mobile Applications
... of genetic algorithms for training neural networks used in secured Business Intelligence Mobile ...a genetic algorithm based training. The design of these algorithms is ...that genetic ...
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ONCOGENES CLASSIFICATION MEASURED BY MICROARRAY USING GENETIC ALGORITHMS
... Due to the great amount and complexity of the in- volved information, the tools based on the conventional computation have shown to be limited in the approach of complex biological problems. One of the explanations for ...
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A New Technique to Manage Big Bioinformatics Data Using Genetic Algorithms
... studying genetic information field in bioinformatics domain (the computer science field, genetic biology field, and DNA) which has increased in past thirty ...efficient algorithms such as ...
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Genetic Algorithms for a Parameter Estimation of a Fermentation Process Model: A Comparison
... using genetic algorithms is performed. A comparison of three genetic algorithms, namely simple, modified and multi-population genetic algorithms is ...the genetic ...
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GENETIC ALGORITHMS APPLIED TO ASSET LIABILITY MANAGEMENT
... of genetic algorithms can be found in Finance, particularly in the sub-field of portfolio ...variance. Genetic algorithms are very well suited to perform portfolio optimization because the ...
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Gene Ontology Classification: Building High-level Knowledge using Genetic Algorithms
... Due to the great amount of information and its complexity, tools based on conventional computation have shown limita- tions to model complex biological problems. One explanation for such difficulty is the inefficiency of ...
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Determination of Turbulence Coefficient using Genetic Algorithms
... (Genetic Algorithms), GP (Genetic Programming), SA (Simulated Annealing), SCE (Shuffled Complex Evolution) method developed at the UA (University of Arizona) and ANN (Artificial Neural ...
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Using Genetic Algorithms for Building Metrics of Collaborative Systems
... of genetic algorithms is to represent the solutions of a problem in the form of chromosomes and to work, at each step, with a fixed number of chromosomes, forming a ...solution. Genetic ...
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Phase-Only Planar Antenna Array Synthesis with Fuzzy Genetic Algorithms
... fuzzy genetic algorithms (FGAs) by optimizing phase excitation coefficients to best meet a desired radiation ...fuzzy genetic algorithms (FGAs), the optimizing algorithm is obtained by ...
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Affine image registration using genetic algorithms and evolutionary strategies
... Evolutionary Computation (EC) covers all aspects of the simulation of evolutionary pro- cess in computer systems. It is quite a recent and tremendously growing field as well as an optimization process. The term itself ...
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A Facility Layout Planner Tool Based on Genetic Algorithms
... This paper intends to give a detailed overview of the methodologies used to tackle Facility Layout Planning prob- lems (FLP), which arise from the need to organize facilities in the shop-floor in the most efficient way ...
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Dependency structure matrix, genetic algorithms, and effective recombination
... of genetic algorithms. The proposed genetic algorithm design utilizes a matrix repre- sentation of an interaction graph to analyze and explicitly decompose the ...model-building genetic ...
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SCHEMATIC BUS TRANSIT MAPS FOR THE WEB USING GENETIC ALGORITHMS
... The goal on this dissertation is to explore the use of automatic generation of schematic maps into real time web applications in order to produce customized schematic maps. Since the metro layout problem has been proven ...
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Modified Genetic Algorithms Based Solution To Subset Sum Problem
... Abstract—Subset Sum Problem (SSP) is an NP Complete problem which finds its application in diverse fields. The work suggests the solution of above problem with the help of genetic Algorithms (GAs). The work ...
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Musical pattern extraction using genetic algorithms
... Genetic algorithms are parallel and stochastic search algorithms inspired by the evolution theory and molecular biology, which allow the evolution of a set of potential solutions to a ...typical ...
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Computing strategy adaptation for genetic algorithms
... self-adaptive genetic optimiza- tion ...individual genetic algorithms with a set of operators and compete against each other on the principles of natural ...as genetic algorithms), but ...
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AN INTRODUCTION TO GENETIC ALGORITHMS
... The question is how to represent these four values. A simple way to do this is to simply have an array of four values (integers or floating point numbers, either way). However, for genetic algorithms it is ...
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Approach Multiclass SVM Utilizing Genetic Algorithms
... en genetic algorithms, in order to achieve high classification efficiency for multiclass ...by genetic algorithms with the aim of obtaining a strategy multiclass SVM with a reasonable and ...
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DESIGN AND OPTIMIZATION OF VALVELESS MICROPUMPS BY USING GENETIC ALGORITHMS APPROACH
... This paper presents a design optimization of valveless micropump using Genetic Algorithms (GA). The micropump is designed with a diaphragm, pumping chamber and diffuser/nozzle element functions as inlet and ...
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Hybrid Genetic Algorithms: A Review
... The selection of an appropriate approximation model to replace the real function is an important step in ensuring that the optimization problem is solved efficiently. Neural network [21 ch. 8] models have widely been ...
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