Search results for "evolution"

showing 10 items of 11096 documents

Interactive Multiple Criteria Decision Making based on preference driven Evolutionary Multiobjective Optimization with controllable accuracy

2012

Abstract We present an approach to interactive Multiple Criteria Decision Making based on preference driven Evolutionary Multiobjective Optimization with controllable accuracy. The approach relies on formulae for lower and upper bounds on coordinates of the outcome of an arbitrary efficient variant corresponding to preference information expressed by the Decision Maker. In contrast to earlier works on that subject, here lower and upper bounds can be calculated and their accuracy controlled entirely within evolutionary computation framework. This is made possible by exploration of not only the region of feasible variants – a standard within evolutionary optimization, but also the region of i…

ta113Mathematical optimizationInformation Systems and ManagementGeneral Computer ScienceComputationta111Contrast (statistics)Interactive evolutionary computationManagement Science and Operations ResearchMulti-objective optimizationOutcome (game theory)Industrial and Manufacturing EngineeringEvolutionary computationModeling and SimulationPreference (economics)Evolutionary programmingMathematicsEuropean Journal of Operational Research
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Genetic programming through bi-objective genetic algorithms with a study of a simulated moving bed process involving multiple objectives

2013

A new bi-objective genetic programming (BioGP) technique has been developed for meta-modeling and applied in a chromatographic separation process using a simulated moving bed (SMB) process. The BioGP technique initially minimizes training error through a single objective optimization procedure and then a trade-off between complexity and accuracy is worked out through a genetic algorithm based bi-objective optimization strategy. A benefit of the BioGP approach is that an expert user or a decision maker (DM) can flexibly select the mathematical operations involved to construct a meta-model of desired complexity or accuracy. It is also designed to combat bloat - a perennial problem in genetic …

ta113Mathematical optimizationMeta-optimizationArtificial neural networkComputer scienceta111Evolutionary algorithmGenetic programmingOverfittingMulti-objective optimizationSimulation-based optimizationGenetic algorithmMetaheuristicSoftwareApplied Soft Computing
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Ensemble strategies in Compact Differential Evolution

2011

Differential Evolution is a population based stochastic algorithm with less number of parameters to tune. However, the performance of DE is sensitive to the mutation and crossover strategies and their associated parameters. To obtain optimal performance, DE requires time consuming trial and error parameter tuning. To overcome the computationally expensive parameter tuning different adaptive/self-adaptive techniques have been proposed. Recently the idea of ensemble strategies in DE has been proposed and favorably compared with some of the state-of-the-art self-adaptive techniques. Compact Differential Evolution (cDE) is modified version of DE algorithm which can be effectively used to solve …

ta113Mathematical optimizationStochastic processComputer scienceDifferential evolutionCrossoverGlobal optimizationEvolutionary computation2011 IEEE Congress of Evolutionary Computation (CEC)
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Super-fit and population size reduction in compact Differential Evolution

2011

Although Differential Evolution is an efficient and versatile optimizer, it has a wide margin of improvement. During the latest years much effort of computer scientists studying Differential Evolution has been oriented towards the improvement of the algorithmic paradigm by adding and modifying components. In particular, two modifications lead to important improvements to the original algorithmic performance. The first is the super-fit mechanism, that is the injection at the beginning of the optimization process of a solution previously improved by another algorithm. The second is the progressive reduction of the population size during the evolution of the population. Recently, the algorithm…

ta113Mathematical optimizationeducation.field_of_studyMeta-optimizationFitness landscapeComputer sciencePopulation-based incremental learningPopulationContext (language use)Reduction (complexity)Differential evolutionAlgorithm designeducationAlgorithm2011 IEEE Workshop on Memetic Computing (MC)
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Synchronous R-NSGA-II: An Extended Preference-Based Evolutionary Algorithm for Multi-Objective Optimization

2015

Classical evolutionary multi-objective optimization algorithms aim at finding an approx- imation of the entire set of Pareto optimal solutions. By considering the preferences of a decision maker within evolutionary multi-objective optimization algorithms, it is possible to focus the search only on those parts of the Pareto front that satisfy his/her preferences. In this paper, an extended preference-based evolutionary algorithm has been proposed for solving multi-objective optimiza- tion problems. Here, concepts from an interactive synchronous NIMBUS method are borrowed and combined with the R-NSGA-II algorithm. The proposed synchronous R-NSGA-II algorithm uses preference information provid…

ta113Mathematical optimizationinteractive multi-objective optimizationApplied MathematicsEvolutionary algorithmApproxDecision makerMulti-objective optimizationscalarizing functionSet (abstract data type)Pareto optimalevolutionary multi-objective optimizationpreference-based evolutionary algorithmsFocus (optics)Preference (economics)Information SystemsMathematicsInformatica
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Evaluating the performance of artificial neural networks for the classification of freshwater benthic macroinvertebrates

2014

Abstract Macroinvertebrates form an important functional component of aquatic ecosystems. Their ability to indicate various types of anthropogenic stressors is widely recognized which has made them an integral component of freshwater biomonitoring. The use of macroinvertebrates in biomonitoring is dependent on manual taxa identification which is currently a time-consuming and cost-intensive process conducted by highly trained taxonomical experts. Automated taxa identification of macroinvertebrates is a relatively recent research development. Previous studies have displayed great potential for solutions to this demanding data mining application. In this research we have a collection of 1350 …

ta113Radial basis function networkEcologyArtificial neural networkComputer sciencebusiness.industryApplied MathematicsEcological Modelingta1172PerceptronMachine learningcomputer.software_genreBackpropagationComputer Science ApplicationsProbabilistic neural networkIdentification (information)Computational Theory and MathematicsModeling and SimulationMultilayer perceptronConjugate gradient methodta1181Artificial intelligencebusinesscomputerEcology Evolution Behavior and SystematicsEcological Informatics
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JIMWLK and beyond: From concepts to observables

2016

Volume: 112 Host publication title: 6th International Conference on Physics Opportunities at an Electron-Ion Collider The Color Glass Condensate and its associated evolution equation, the JIMWLK equation have applications to many observables far beyond totally inclusive observables. The phenomenology is so rich that little has been done to explore beyond scaling behavior of correlators. We show first examples that exemplify the considerations necessary to access additional information both experimentally and theoretically and demonstrate that the Wilson line correlators appearing throughout make it imperative to consistently take into account that one is dealing with correlators of group el…

ta114Operations research010308 nuclear & particles physicsComputer sciencePhysicsQC1-999scalingCOLOR GLASS CONDENSATEObservable114 Physical sciences01 natural sciencesSTATESMALL X EVOLUTIONColor-glass condensateWilson loopTheoretical physicsODDERONevolution equation0103 physical sciencesEvolution equationcolor glass condensate010306 general physicsScalingN-CEPJ Web of Conferences
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Visual understanding of divergence and curl: Visual cues promote better learning

2019

Prior research has shown that students struggle to indicate whether vector field plots have zero or non-zero curl or divergence. In an instruction-based eye-tracking study, we investigated whether visual cues (VC) provided in the vector field plot can foster students’ understanding of these concepts. The VC were only present during instruction and highlighted conceptual information about vector decomposition and partial derivatives. Thirty-two physics majors were assigned to two groups, one was instructed with VC about the problemsolving strategy, and one without. The results show that students in VC-condition performed better, responded with higher confidence, experienced less mental effor…

ta114visualisointiBiologyDivergencevisualisationproblem solvingCurl (programming language)Evolutionary biologyvektorit (matematiikka)ta516ongelmanratkaisuvector fieldsSensory cuecomputercomputer.programming_language2018 Physics Education Research Conference Proceedings
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Methane-oxidizing and photoautotrophic bacteria are major producers in a humic lake with large anoxic hypolimnion

2011

Heterotrophic processes are considered to prevail in lakes with high terrestrial loading and a high content of dissolved organic carbon. However, previous studies have shown abundant methanotrophic bacteria (MOB) and photoautotrophic green sulphur bacteria (GSB) in some boreal lakes. We used genetic and lipid biomarkers to follow the seasonal succession of the abundance and carbon biomass of the major bacterial groups in Lake Mekkojarvi, a small Finnish polyhumic lake with a large anoxic hypolimnion. Biomarkers were based on length heterogeneity analysis of 16S rRNA gene amplification by polymerase chain reaction (PCR) (LH-PCR) and on phospholipid fatty acid (PLFA) analysis. Representative …

ta1183HeterotrophAquatic ScienceBiologybiology.organism_classificationAnoxic watersActinobacteriaBotanyDissolved organic carbonPhytoplanktonAutotrophHypolimnionEcology Evolution Behavior and SystematicsBacteriaAquatic Microbial Ecology
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Genome size evolution in macroparasites.

2014

Reduction in genome size has been associated not only with a parasitic lifestyle in intracellular microparasites but also in some macroparasitic insects and nematodes. We collected the available data on genome size for flatworms, annelids, nematodes and arthropods, compared those with available data for the phylogenetically closest free-living taxa and found evidence of smaller genome sizes for parasites in six of nine comparisons. Our results suggest that despite great differences in evolutionary history and life cycles, parasitism as a lifestyle promotes convergent genome size reduction in macroparasites. We discuss factors that could be associated with small genome size in parasites whic…

ta1184ParasitismBiologyGenomeEvolution MolecularInfectious DiseasesTaxonGenomic reductionGenome SizeEvolutionary biologyMacroparasiteParasitismMacroparasiteta1181AnimalsParasitologyParasitesDatabases Nucleic AcidGenome sizeMicroparasiteConverged evolutionInternational journal for parasitology
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