Search results for "A* algorithm"

showing 10 items of 2538 documents

Optimizing Query Perturbations to Enhance Shape Retrieval

2020

3D Shape retrieval algorithms use shape descriptors to identify shapes in a database that are the most similar to a given key shape, called the query. Many shape descriptors are known but none is perfect. Therefore, the common approach in building 3D Shape retrieval tools is to combine several descriptors with some fusion rule. This article proposes an orthogonal approach. The query is improved with a Genetic Algorithm. The latter makes evolve a population of perturbed copies of the query, called clones. The best clone is the closest to its closest shapes in the database, for a given shape descriptor. Experimental results show that improving the query also improves the precision and complet…

050101 languages & linguisticsComputer scienceInformationSystems_INFORMATIONSTORAGEANDRETRIEVALPopulationComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Search engineCompleteness (order theory)Genetic algorithm0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciences[INFO]Computer Science [cs]educationMassively parallelComputingMilieux_MISCELLANEOUSThesaurus (information retrieval)education.field_of_studyCloning (programming)business.industry05 social sciencesPattern recognitionKey (cryptography)020201 artificial intelligence & image processingArtificial intelligencebusiness
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Reverse-safe data structures for text indexing

2021

We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optim…

050101 languages & linguisticsComputer sciencedata structure02 engineering and technologyprivacySet (abstract data type)combinatoric0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesPattern matchingSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazionialgorithmSettore INF/01 - Informatica05 social sciencesSearch engine indexingINF/01 - INFORMATICAdata miningData structureMatrix multiplicationcombinatoricsExponent020201 artificial intelligence & image processingdata structure; algorithm; combinatorics; de Bruijn graph; data mining; privacyAlgorithmAdversary modelde Bruijn graphInteger (computer science)
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An Interactive Framework for Offline Data-Driven Multiobjective Optimization

2020

We propose a framework for solving offline data-driven multiobjective optimization problems in an interactive manner. No new data becomes available when solving offline problems. We fit surrogate models to the data to enable optimization, which introduces uncertainty. The framework incorporates preference information from a decision maker in two aspects to direct the solution process. Firstly, the decision maker can guide the optimization by providing preferences for objectives. Secondly, the framework features a novel technique for the decision maker to also express preferences related to maximum acceptable uncertainty in the solutions as preferred ranges of uncertainty. In this way, the d…

050101 languages & linguisticsDecision support systemMathematical optimizationOptimization problemdecision supportComputer scienceEvolutionary algorithmGaussian processespäätöksentukijärjestelmät02 engineering and technologyMulti-objective optimizationdecision makingData-driven0202 electrical engineering electronic engineering information engineeringmetamodelling0501 psychology and cognitive sciencessurrogateInteractive visualization05 social sciencesgaussiset prosessitmonitavoiteoptimointiMetamodelingKriging020201 artificial intelligence & image processingdecomposition-based MOEAkriging-menetelmäCognitive load
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A New Paradigm in Interactive Evolutionary Multiobjective Optimization

2020

Over the years, scalarization functions have been used to solve multiobjective optimization problems by converting them to one or more single objective optimization problem(s). This study proposes a novel idea of solving multiobjective optimization problems in an interactive manner by using multiple scalarization functions to map vectors in the objective space to a new, so-called preference incorporated space (PIS). In this way, the original problem is converted into a new multiobjective optimization problem with typically fewer objectives in the PIS. This mapping enables a modular incorporation of decision maker’s preferences to convert any evolutionary algorithm to an interactive one, whe…

050101 languages & linguisticsMathematical optimizationComputer sciencemedia_common.quotation_subjectdecision makerEvolutionary algorithmpäätöksentukijärjestelmätevoluutiolaskentapreference information02 engineering and technologySpace (commercial competition)Multi-objective optimizationoptimointiachievement scalarizing functionsalgoritmit0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesQuality (business)evolutionary algorithmsFunction (engineering)media_commonbusiness.industry05 social sciencesinteractive methodsModular designDecision makermonitavoiteoptimointiPreference020201 artificial intelligence & image processingbusiness
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2019

Worries about possible harmful effects of new technologies (modern health worries) have intensely been investigated in the last decade. However, the comparability of translated self-report measures across countries is often problematic. This study aimed to overcome this problem by developing psychometrically sound brief versions of the widely used 25-item Modern Health Worries Scale (MHWS) suitable for multi-country use. Based on data of overall 5,176 individuals from four European countries (England, Germany, Hungary, Sweden), Ant Colony Optimization was used to identify the indicators that optimize model fit and measurement invariance across countries. Two scales were developed. A short (…

050103 clinical psychologyMultidisciplinaryPublic economicsPsychometricsEmerging technologiesAnt colony optimization algorithms05 social sciencesComparabilityItem selection050109 social psychologyCross-cultural studies0501 psychology and cognitive sciencesMeasurement invariancePsychologyPLOS ONE
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Fuzzy Portfolio Selection Models for Dealing with Investor’s Preferences

2017

This chapter provides an overview of the authors’ previous work about dealing with investor’s preferences in the portfolio selection problem. We propose a fuzzy model for dealing with the vagueness of investor preferences on the expected return and the assumed risk, and then we consider several modifications to include additional constraints and goals.

050208 finance021103 operations researchActuarial scienceFinancial economicsComputer science05 social sciencesFuzzy model0211 other engineering and technologiesVagueness02 engineering and technologyFuzzy logicInvestor profile0502 economics and businessPortfolioExpected returnPortfolio optimizationSelection (genetic algorithm)
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Impact of decision horizon on post-prognostics maintenance and missions scheduling: a railways case study

2021

International audience; In this paper, we propose a study of the decision horizon duration for rolling stock mission assignment and maintenance planning in a prognostics and health management (PHM) context. The aim is to determine the best decision horizon duration that allows the con- struction of a suitable schedule that assigns railway vehicles to missions and integrates required maintenance operations accord- ing to the current and future health of the vehicles. A genetic algorithm is used to minimize the overall cost of the joint schedule as a function of the decision horizon. The results are compared to three proposed heuristics to study the influence of the resolution method on the d…

050210 logistics & transportation0209 industrial biotechnologyScheduleOperations researchHorizon (archaeology)Computer science05 social sciences[INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS]TransportationContext (language use)02 engineering and technologyScheduling (computing)[SPI.AUTO]Engineering Sciences [physics]/Automatic020901 industrial engineering & automationMechanics of Materials0502 economics and businessAutomotive EngineeringGenetic algorithmPrognosticsDuration (project management)Heuristics
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Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design.

2016

Various studies have emphasized the interesting advantages related to the use of new transition curves for improving the geometric design of highway horizontal alignments. In a previous paper, one of the writers proposed a polynomial curve, called a polynomial parametric curve (PPC), proving its efficiency in solving several design problems characterized by a very complex geometry (egg-shaped transition, transition between reversing circular curves, semidirect and inner-loop connections, and so on). The PPC also showed considerable advantages from a dynamic perspective, as evidenced by the analysis of the main dynamic variables related to motion (as well as rate of change of radial accelera…

050210 logistics & transportationPolynomialMathematical optimizationFitness function05 social sciencesPerspective (graphical)Motion (geometry)020101 civil engineering02 engineering and technologyTransition curve0201 civil engineeringComputer Science ApplicationsGeometric designComplex geometryGenetic algorithmGenetic algorithms Horizontal alignment Polynomial curve Transition curve0502 economics and businessHorizontal alignment.Polynomial curveSettore ICAR/04 - Strade Ferrovie Ed AeroportiReversingParametric equationAlgorithmCivil and Structural EngineeringMathematics
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Exploring Relationships Between Anthropometry, Body Composition, Maturation, and Selection for Competition: A Study in Youth Soccer Players

2021

PurposeThe purpose of this study was to analyze variations of selection for competition between late and early mature players and test the relationships between anthropometry, body composition, maturation, and selection for competition.MethodsSeventy-nine youth soccer players from under-11 to under-14 participated in this study, over 6 months. Body composition and maturity offset were estimated based on anthropometric data collected. Participants were also monitored for their number of matches as starters and time of play accrued in minutes.ResultsMinutes played had large correlation coefficients with maturity offset (r = 0.58), and leg length and sitting height interaction (r = 0.56). Mult…

11035 Institute of General PracticefootballPhysiologymedia_common.quotation_subject610 Medicine & healthBiologyCompetition (biology)lcsh:PhysiologyCorrelation03 medical and health sciences2737 Physiology (medical)0302 clinical medicinePhysiology (medical)Linear regressiontalent developmentmotor developmentSelection (genetic algorithm)media_commonOriginal Researchlcsh:QP1-981youngmaturationLeg length1314 Physiology030229 sport sciencesAnthropometryComposition (combinatorics)Maturity (psychological)030217 neurology & neurosurgeryperformanceDemography
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"Exclusion contour(obs.) 9 : Meff" of "Search for squarks and gluinos in final states with jets and missing transverse momentum using 36 fb$^{-1}$ of…

2018

Observed 95% CL exclusion contours from Meff-based searches on the gluino mass and the mass gap ratio x in a SUSY scenario where gluinos are produced in pairs and decay via an intermediate lightest chargino or second lightest neutralino to the lightest neutralino, $\tilde{g} \rightarrow qq \tilde{\chi}_{1}^{\pm} \rightarrow qq W^{\pm} \tilde{\chi}_{1}^{0}$, or $\tilde{g} \rightarrow qq \tilde{\chi}_{2}^{0} \rightarrow qq Z/h \tilde{\chi}_{1}^{0}$.

13000.0High Energy Physics::LatticeCLSHigh Energy Physics::PhenomenologyP P --> GLUINO GLUINO XHigh Energy Physics::ExperimentComputer Science::Data Structures and Algorithms
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