Search results for "Computational Intelligence"

showing 10 items of 50 documents

Hydrological post-processing based on approximate Bayesian computation (ABC)

2019

[EN] This study introduces a method to quantify the conditional predictive uncertainty in hydrological post-processing contexts when it is cumbersome to calculate the likelihood (intractable likelihood). Sometimes, it can be difficult to calculate the likelihood itself in hydrological modelling, specially working with complex models or with ungauged catchments. Therefore, we propose the ABC post-processor that exchanges the requirement of calculating the likelihood function by the use of some sufficient summary statistics and synthetic datasets. The aim is to show that the conditional predictive distribution is qualitatively similar produced by the exact predictive (MCMC post-processor) or …

Mathematical optimizationINGENIERIA HIDRAULICAEnvironmental Engineering010504 meteorology & atmospheric sciencesComputer scienceHydrological modelling0208 environmental biotechnologyComputational intelligence02 engineering and technologySummary statistic01 natural sciencesFree-likelihood approachsymbols.namesakeHydrological forecastingEnvironmental ChemistryProbabilistic modellingSafety Risk Reliability and QualityUncertainty analysis0105 earth and related environmental sciencesGeneral Environmental ScienceWater Science and TechnologyProbabilistic modellingMarkov chain Monte Carlo020801 environmental engineeringBenchmark (computing)symbolsUncertainty analysisApproximate Bayesian computationSummary statisticsLikelihood functionSettore SECS-S/01 - Statistica
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Learning Automata-Based Solutions to Stochastic Nonlinear Resource Allocation Problems

2009

“Computational Intelligence” is an extremely wide-ranging and all-encompassing area. However, it is fair to say that the strength of a system that possesses “Computational Intelligence” can be quantified by its ability to solve problems that are intrinsically hard. One such class of NP-Hard problems concerns the so-called family of Knapsack Problems, and in this Chapter, we shall explain how a sub-field of Artificial Intelligence, namely that which involves “Learning Automata”, can be used to produce fast and accurate solutions to “difficult” and randomized versions of the Knapsack problem (KP).

Mathematical optimizationNonlinear systemClass (computer programming)Learning automataKnapsack problemContinuous knapsack problemResource allocationStochastic optimizationComputational intelligenceMathematics
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Humorist Bot: Bringing Computational Humour in a Chat-Bot System

2008

A conversational agent, capable to have a ldquosense of humourrdquo is presented. The agent can both generate humorous sentences and recognize humoristic expressions introduced by the user during the dialogue. Humorist Bot makes use of well founded techniques of computational humor and it has been implemented using the ALICE framework embedded into an Yahoo! Messenger client. It includes also an avatar that changes the face expression according to humoristic content of the dialogue.

MultimediaComputer scienceComputingMilieux_PERSONALCOMPUTINGComputational humorFace (sociological concept)Computational intelligencecomputer.software_genreKnowledge-based systemsIntelligent agentHuman–computer interactionchatbot wordnet lsaUser interfaceDialog systemcomputerAvatar2008 International Conference on Complex, Intelligent and Software Intensive Systems
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A real-time network architecture for biometric data delivery in Ambient Intelligence

2012

Ambient Intelligent applications involve the deployment of sensors and hardware devices into an intelligent environment surrounding people, meeting users’ requirements and anticipating their needs (Ambi- ent Intelligence-AmI). Biometrics plays a key role in surveillance and security applications. Fingerprint, iris and voice/speech traits can be acquired by contact, contact-less, and at-a-distance sensors embedded in the environment. Biometric traits transmission and delivery is very critical and it needs real-time transmission net- work with guaranteed performance and QoS. Wireless networks become suitable for AmI if they are able to satisfy real-time communication and security system requi…

Network architectureAmbient intelligenceGeneral Computer ScienceBiometricsbusiness.industryComputer scienceWireless networkQuality of serviceComputational intelligenceAutomationAmbient Intelligence Efficient wireless sensor networks Real-time scheduling Biometric traits processingSoftware deploymentEmbedded systemWirelessIntelligent environmentbusinessJournal of Ambient Intelligence and Humanized Computing
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Classifier Optimized for Resource-constrained Pervasive Systems and Energy-efficiency

2017

Computational intelligence is often used in smart environment applications in order to determine a user’scontext. Many computational intelligence algorithms are complex and resource-consuming which can beproblematic for implementation devices such as FPGA:s, ASIC:s and low-level microcontrollers. Thesetypes of devices are, however, highly useful in pervasive and mobile computing due to their small size,energy-efficiency and ability to provide fast real-time responses. In this paper, we propose a classi-fier, CORPSE, specifically targeted for implementation in FPGA:s, ASIC:s or low-level microcontrollers.CORPSE has a small memory footprint, is computationally inexpensive, and is suitable for…

Parallel computingMicrocontrollerEnergy-efficientGeneral Computer ScienceComputer scienceDistributed computingComputational intelligenceCellular AutomataClassifierlcsh:QA75.5-76.95EmbeddedAnnan elektroteknik och elektronikEnergy-savingFPGAOther Electrical Engineering Electronic Engineering Information Engineeringbusiness.industryComputer SciencesComputational MathematicsDatavetenskap (datalogi)Embedded systemPervasive systemsSmart environmentlcsh:Electronic computers. Computer sciencebusinessClassifier (UML)Efficient energy use
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A New Hybrid Mutation Operator for Multiobjective Optimization with Differential Evolution

2011

Differential evolution has become one of the most widely used evolution- ary algorithms in multiobjective optimization. Its linear mutation operator is a sim- ple and powerful mechanism to generate trial vectors. However, the performance of the mutation operator can be improved by including a nonlinear part. In this pa- per, we propose a new hybrid mutation operator consisting of a polynomial based operator with nonlinear curve tracking capabilities and the differential evolution’s original mutation operator, to be efficiently able to handle various interdependencies between decision variables. The resulting hybrid operator is straightforward to implement and can be used within most evoluti…

Pareto optimalityMathematical optimizationEvolutionary algorithmComputational intelligenceMOEA/DNonlinearGenetic operatorEvolutionary algorithmsMulti-objective optimizationPolynomialTheoretical Computer ScienceDEOperator (computer programming)Evolutionary algorithms; DE; Nonlinear; Multi-criteria optimization; Polynomial; Pareto optimality; MOEA/DPareto-optimaalisuusMathematicsMatematikMulti-criteria optimizationState (functional analysis)monitavoiteoptimointiNonlinear systemDifferential evolutionGeometry and TopologyAlgorithmSoftwareMathematics
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Prelogical Test: An Alternative Tool for Early Detection of Learning Difficulties

2014

Abstract Difficulties during the preschool age commonly lead to children who cannot solve problems, organize information and create meaning. It is necessary to predict factors that may affect their future learning. The aim is to develop an evaluation tool, to be applied in groups and that can easily evaluate results, to detect future learning problems in children of 3-6 years old. Computational intelligence techniques could contribute greatly to analyze results and to detect patterns that otherwise would not be apparent. Two protocols were implemented: an Indirect Variables Protocol (IVP) which captures children's personal data, and a Direct Variables Protocol (DVP) that assesses the graphi…

Protocol (science)Learning difficultiesComputer sciencebusiness.industryComputational intelligenceSample (statistics)Machine learningcomputer.software_genreTest (assessment)Variable (computer science)Prelogical TestGeneral Materials ScienceIsolation (database systems)Artificial intelligenceearly detectionCluster analysisbusinesscomputerMeaning (linguistics)Procedia - Social and Behavioral Sciences
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A Study on scale factor in distributed differential evolution.

2011

This paper proposes the employment of multiple scale factor values within distributed differential evolution structures. Four different scale factor schemes are proposed, tested, compared and analyzed. Two schemes simply employ multiple scale factor values and two also include an update logic during the evolution. The four schemes have been integrated for comparison within three recently proposed distributed differential evolution structures and tested on several various test problems. Numerical results show that, on average, the employment of multiple scale factors is beneficial since in most cases it leads to significant improvements in performance with respect to standard distributed alg…

Scheme (programming language)ta113distributed algorithmsMathematical optimizationInformation Systems and ManagementScale (ratio)Computer sciencedifferential evolutionEvolutionary algorithmcomputational intelligence optimizationevolutionary algorithmsstructured populationsScale factorComputer Science ApplicationsTheoretical Computer ScienceArtificial IntelligenceControl and Systems EngineeringSimple (abstract algebra)Distributed algorithmDifferential evolutionoptimization algorithmsscale factorcomputerSoftwarecomputer.programming_language
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Bot or not? a case study on bot recognition from web session logs

2018

This work reports on a study of web usage logs to verify whether it is possible to achieve good recognition rates in the task of distinguishing between human users and automated bots using computational intelligence techniques. Two problem statements are given, offline (for completed sessions) and on-line (for sequences of individual HTTP requests). The former is solved with several standard computational intelligence tools. For the second, a learning version of Wald’s sequential probability ratio test is used.

Sequential decisionComputer sciencebusiness.industryProblem statementComputational intelligence02 engineering and technologyMachine learningcomputer.software_genreSequential decisionClassificationSession (web analytics)Task (project management)Work (electrical)020204 information systemsSequential probability ratio test0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingWeb usageArtificial intelligencebusinessClassification; Sequential decision; Web bot recognitioncomputerWeb bot recognition
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Sviluppi della Intelligenza Computazionale: l'esempio del Sarcasm Detection

2016

Dopo un periodo prolungato in cui vigeva uno scarto persistente tra l’ottimismo dato dai grandi proclami di ricerca e la scarsità e frammentarietà di risultati veri e tangibili, viviamo (finalmente) nell’era delle grandi conquiste dell’Intelligenza Artificiale

Settore INF/01 - InformaticaComputational Intelligence Sarcasm Detection
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