Search results for "programming"

showing 10 items of 3090 documents

DAE-GP

2020

Estimation of distribution genetic programming (EDA-GP) algorithms are metaheuristics where sampling new solutions from a learned probabilistic model replaces the standard mutation and recombination operators of genetic programming (GP). This paper presents DAE-GP, a new EDA-GP which uses denoising autoencoder long short-term memory networks (DAE-LSTMs) as probabilistic model. DAE-LSTMs are artificial neural networks that first learn the properties of a parent population by mapping promising candidate solutions to a latent space and reconstructing the candidate solutions from the latent space. The trained model is then used to sample new offspring solutions. We show on a generalization of t…

education.field_of_studyArtificial neural networkbusiness.industryComputer scienceOffspringPopulationProbabilistic logicGenetic programmingStatistical model0102 computer and information sciences02 engineering and technologyMachine learningcomputer.software_genre01 natural sciencesTree (data structure)Estimation of distribution algorithm010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligencebusinesseducationcomputerMetaheuristicProceedings of the 2020 Genetic and Evolutionary Computation Conference
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PEMODELAN GEOGRAPHICALLY WEIGHTED REGRESSION (GWR) PADA PERSENTASE KRIMINALITAS DI PROVINSI JAWA TIMUR TAHUN 2017

2020

Crime is everything that exists in Indonesia. Based on BPS data in 2018, East Java Province ranks first in the Province of North Sumatra and the Special Capital Region of Jakarta. This research was conducted to determine the factors that support crime in each Regency / City of East Java Province. The method used in this research is Weighted Geographic Regression (GWR). Geographically Weighted Regression (GWR) is one of the statistical methods used to model variable responses with regional or area-based predictor variables. Based on the GWR results, it is recognized as a variable Population Density Percentage (X1), Open Unemployment Rate (X2), Poor Population (X3), Population who are Victims…

education.field_of_studyCoefficient of determinationJavaPopulationPopulation densityRegressionGeographically Weighted RegressionVariable (computer science)GeographyStatisticsHuman Development Indexeducationcomputercomputer.programming_languageIndonesian Journal of Statistics and Its Applications
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Scatter Search for the Point-Matching Problem in 3D Image Registration

2008

Scatter search is a population-based method that has recently been shown to yield promising outcomes for solving combinatorial and nonlinear optimization problems. Based on formulations originally proposed in the 1960s for combining decision rules and problem constraints, such as the surrogate constraint method, scatter search uses strategies for combining solution vectors that have proved effective in a variety of problem settings. We present a scatter-search implementation designed to find high-quality solutions for the 3D image-registration problem, which has many practical applications. This problem arises in computer vision applications when finding a correspondence or transformation …

education.field_of_studyComputer scienceHeuristic (computer science)business.industryPopulationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONGeneral EngineeringImage registrationPoint set registrationMachine learningcomputer.software_genreEvolutionary computationNonlinear programmingRobustness (computer science)Artificial intelligenceeducationbusinessMetaheuristicAlgorithmcomputerINFORMS Journal on Computing
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On sampling error in evolutionary algorithms

2021

The initial population in evolutionary algorithms (EAs) should form a representative sample of all possible solutions (the search space). While large populations accurately approximate the distribution of possible solutions, small populations tend to incorporate a sampling error. A low sampling error at initialization is necessary (but not sufficient) for a reliable search since a low sampling error reduces the overall random variations in a random sample. For this reason, we have recently presented a model to determine a minimum initial population size so that the sampling error is lower than a threshold, given a confidence level. Our model allows practitioners of, for example, genetic pro…

education.field_of_studyDistribution (mathematics)Population sizePopulationStatisticsEvolutionary algorithmInitializationSmall population sizeGenetic programmingeducationConfidence intervalMathematicsProceedings of the Genetic and Evolutionary Computation Conference Companion
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EMERGING PROPERTIES IN POPULATION DYNAMICS WITH DIFFERENT TIME SCALES

1995

The aim of this work is to show that at the population level, emerging properties may occur as a result of the coupling between the fast micro-dynamics and the slow macrodynamics. We studied a prey-predator system with different time scales in a heterogeneous environment. A fast time scale is associated to the migration process on spatial patches and a slow time scale is associated to the growth and the interactions between the species. Preys go on the spatial patches on which some resources are located and can be caught by the predators on them. The efficiency of the predators to catch preys is patch-dependent. Preys can be more easily caught on some spatial patches than others. Perturbat…

education.field_of_studyEcologyEcologyDifferential equationApplied MathematicsAggregate (data warehouse)PopulationScale (descriptive set theory)General MedicineBiologyAgricultural and Biological Sciences (miscellaneous)Nonlinear systemCoupling (computer programming)Ordinary differential equationPerturbation theoryeducationBiological systemJournal of Biological Systems
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On the Bias of Syntactic Geometric Recombination in Genetic Programming and Grammatical Evolution

2015

For fixed-length binary representations as used in genetic algorithms, standard recombination operators (e.g.,~one-point crossover) are unbiased. Thus, the application of recombination only reshuffles the alleles and does not change the statistical properties in the population. Using a geometric view on recombination operators, most search operators for fixed-length strings are geometric, which means that the distances between offspring and their parents are less than, or equal to, the distance between their parents. In genetic programming (GP) and grammatical evolution (GE), the situation is different since the recombination operators are applied to variable-length structures. Thus, most r…

education.field_of_studyGrammatical evolutionBinary search treePopulationCrossoverBinary numberGenetic programmingeducationRandom walkAlgorithmRecombinationMathematicsProceedings of the 2015 Annual Conference on Genetic and Evolutionary Computation
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Multi-Agent Based Energy Management in Microgrids Using MACSimJX

2019

Excessive growth in electricity consumption has been experienced over the past few years due to an increase in population around the world.This tends to increase the use of renewable energy and randomness of the load. So.it is important to improve the traditional methodologies and techniques applied on microgrid to make it more intelligent. In this paper, multi agent system is employed over autonomous microgrid framework to endorse its intelligence. The Multi-Agent system is simulated in Java Agent Development Environment (JADE) environment and matlab toolbox Simulink is used for the implementation of the microgrid model. Further, MACSimJX is used to communicate between the micro grid and a…

education.field_of_studyJavaEnergy managementComputer scienceProcess (engineering)business.industryDistributed computingMulti-agent systemPopulationJADE (programming language)Renewable energyMicrogrideducationbusinesscomputercomputer.programming_language2019 IEEE Student Conference on Research and Development (SCOReD)
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The Tax Justice Network-Africa v Cabinet Secretary for National Treasury & 2 Others: A Big Win for Tax Justice Activism?

2019

This paper develops an optimization model for selecting a large subsample that improves the representativeness of a simple random sample previously obtained from a population larger than the population of interest. The problem formulation involves convex mixed-integer nonlinear programming (convex MINLP) and is therefore NP-hard. However, the solution is found by maximizing the “constant of proportionality” – in other words, maximizing the size of the subsample taken from a stratified random sample with proportional allocation – and restricting it to a p-value high enough to achieve a good fit to the population of interest using Pearson’s chi-square goodness-of-fit test. The beauty of the m…

education.field_of_studyPopulationStatisticsChi-square testSample (statistics)p-valueeducationSimple random sampleRepresentativeness heuristicStratified samplingMathematicsNonlinear programmingSSRN Electronic Journal
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Intermediaries: bridges across the digital divide

2012

The challenge of bringing developing countries into the “information society” has been traditionally framed as bridging the digital divide. Meeting this challenge has predominantly been through technical solutions aimed at providing physical access to the Internet. Yet, other aspects of the divide such as low literacy rates, gender and religious issues arguably pose bigger hurdles in getting the benefits of the Internet to the vast majority of the population of developing countries. They are seldom aware of the information available on the net and even when they are, they have difficulty using it. To facilitate access and use of the Internet by the population, an intermediary is often neede…

education.field_of_studyPublic Administrationbusiness.industryPopulationDeveloping countryDevelopmentPublic relationsComputer Science ApplicationsBridging (programming)IntermediaryPhysical accessEconomicsThe InternetInformation societybusinessDigital divideeducationInformation Technology for Development
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Scratch detection and removal from static images using simple statistics and genetic algorithms

2002

This paper investigates the removal of line scratches from old movies and gives a twofold contribution. First, it presents simple technique for detecting the scratches, based on an analysis of the statistics of the grey levels. Second, the scratch removal is approached as an optimisation problem, and it is solved by using a genetic algorithm. The method can be classified as a static approach, as it works independently on each single frame of the sequence. It does not require any a-priori knowledge of the absolute position of the scratch, nor an external starting population of chromosomes for the genetic algorithm. The central column of the line scratch once detected is changed with a conven…

education.field_of_studySettore INF/01 - InformaticaComputer sciencePopulationImage processingLinear interpolationObject detectionHardware and ArchitectureScratchStatisticsLine (geometry)Genetic algorithmElectrical and Electronic Engineeringeducationcomputer1707Interpolationcomputer.programming_language
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