Search results for " Inference"

showing 10 items of 337 documents

A BMA Analysis to Assess the Urbanization and Climate Change Impact on Urban Watershed Runoff

2016

Abstract A reliable planning of urban drainage systems aimed at the mitigation of flooding, should take into account the possible change over time of impervious cover in the urban watershed and of the climate features. The present study proposes a methodology to analyze the changing in runoff response for a urban watershed accounting several plausible future states of new urbanization and climate. To this aim, several models simulating the evolution scenario of impervious watershed area and of climate change were adopted. However, it is known that an evolution scenario represents only one of all possible occurrence and it is not necessary the true future state, therefore it is needed to fin…

WatershedBMA analysis010504 meteorology & atmospheric sciencesMeteorologyWatershed area0208 environmental biotechnologyClimate changeurbanizationProbability density function02 engineering and technologyGeneral MedicineBayesian inference01 natural sciences020801 environmental engineeringurban drainage system design.climate changeImpervious surfaceEconometricsEnvironmental scienceSurface runoffEngineering(all)Uncertainty analysis0105 earth and related environmental sciencesProcedia Engineering
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Ontology languages for the semantic web: A never completely updated review

2006

This paper gives a never completely account of approaches that have been used for the research community for representing knowledge. After underlining the importance of a layered approach and the use of standards, it starts with early efforts used for artificial intelligence researchers. Then recent approaches, aimed mainly at the semantic web, are described. Coding examples from the literature are presented in both sections. Finally, the semantic web ontology creation process, as we envision it, is introduced.

Web standardsOntology Inference LayerInformation Systems and ManagementKnowledge representation and reasoningComputer sciencecomputer.internet_protocolProcess ontologyOntology (information science)computer.software_genreSocial Semantic WebOWL-SManagement Information SystemsWorld Wide WebOpen Biomedical OntologiesArtificial IntelligenceSemantic computingSemantic analyticsUpper ontologySemantic Web StackSemantic Webbusiness.industryOntology-based data integrationSuggested Upper Merged OntologyOntology languageOntologyArtificial intelligencebusinessWeb intelligencecomputerOntology alignmentSoftwareNatural language processingKnowledge-Based Systems
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Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)

2020

The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from …

Xylella fastidiosa0106 biological scienceshierarchical Bayesian modelsDiurnal rangeLeaf scorchPlant Sciencelcsh:Plant cultureBayesian inference01 natural sciences010104 statistics & probabilityCovariatemedicinelcsh:SB1-11100101 mathematicsspecies distribution modelsXylella fastidiosabiologySpatial structurealmond leaf scorchintegrated nested Laplace approximation15. Life on landbiology.organism_classificationmedicine.diseaseConfounding effectstochastic partial differential equationGeographyolive quick declineSampling distributionXylella fastidiosaCartography010606 plant biology & botanyFrontiers in Plant Science
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Illumination3.0: A Semantic Annotation Platform Based on Ontology for Medieval Illuminations

2019

National audience

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Knowledge inferenceOntologyAnnotation systemMedieval illuminationComputingMilieux_MISCELLANEOUS[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
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Discovering human mobility from mobile data : probabilistic models and learning algorithms

2020

Smartphone usage data can be used to study human indoor and outdoor mobility. In our work, we investigate both aspects in proposing machine learning-based algorithms adapted to the different information sources that can be collected.In terms of outdoor mobility, we use the collected GPS coordinate data to discover the daily mobility patterns of the users. To this end, we propose an automatic clustering algorithm using the Dirichlet process Gaussian mixture model (DPGMM) so as to cluster the daily GPS trajectories. This clustering method is based on estimating probability densities of the trajectories, which alleviate the problems caused by the data noise.By contrast, we utilize the collecte…

[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Machine LearningDeep LearningDonnées mobiles[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Variational InferenceApprentissage machineMobile DataProbabilistic Models
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Prédire le passé et le futur : rôle des représentations motrices dans l'inférence du mouvement

2012

The effectiveness of the visual system is permitted by a complex processing network, which relies on cortical, sub-cortical and peripheral structures. The purpose of this research is to improve the knowledge of the process sustaining the visual perception of motion, and to produce a computational model able to reproduce the features of human visual tracking of a moving object.This work includes an extensive bibliographic research, and a series of experiments. The thesis consists of two parts:The first part pertains to the determination of performance in the "backward" inference of a partially visible movement. It consist of defining the involvement of exogenous information (retinal signals)…

[SDV.MHEP] Life Sciences [q-bio]/Human health and pathologyBiologic Movement Internal Model Extrapolation Localization Inference Delay CompensationExtrapolation[SHS.PSY]Humanities and Social Sciences/PsychologyBiologic Movement[ PHYS.COND.CM-GEN ] Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other]Compensation DélaisMouvement Biologique Modèle Interne Extrapolation Localisation Inférence Compensation DélaisLocalisationDelay CompensationInférence[SHS.PSY] Humanities and Social Sciences/Psychology[ SHS.PSY ] Humanities and Social Sciences/Psychology[PHYS.COND.CM-GEN] Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other][PHYS.COND.CM-GEN]Physics [physics]/Condensed Matter [cond-mat]/Other [cond-mat.other]LocalizationMouvement Biologique[ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathologyModèle InterneM-PSI/01 - PSICOLOGIA GENERALEInternal Model[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
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Statistical methods for adaptive river basin management and monitoring

2018

Decision-making at different phases of adaptive river basin management planning rely largely on the information that is gained through environmental monitoring. The aim of this thesis was to develop and test statistical assessment tools presumed to be particularly useful for evaluating existing monitoring designs, converting monitoring data into management information and quantifying uncertainties. River basin scale monitoring was performed using a wireless sensor network and a data quality control system and maintenance effort was assessed. National-scale, traditional monitoring data and linear mixed effect modelling were used to estimate the uncertainty in two status class metrics (total …

adaptive managementrehevöityminenbayesilainen menetelmäBayesian inferencepäätöksentekotilastomenetelmätympäristönhoitosensoriverkotvesipolitiikkamonitorointivedenlaatuvesienhoitomonitoringeutrophicationWater Framework Directivestatistical methodsuncertaintyvaluma-alueet
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Jūtu, tātad daru? Uzmanības saistība ar kustību sagatavošanas laiku aktīvās inferences perspektīvā

2021

Pētījuma mērķis ir labāk izprast psiholoģisko procesu pamatprincipus, par teorētisko bāzi izmantojot aktīvo inferenci. Aktīvā inference postulē, ka cilvēka psihe ir saprotama kā hierarhisks maņu prognožu cikls – nevis kā maņu signālu saņēmēja un apstrādātāja, bet kā to aktīva radītāja, kurā uztvere un darbības ir analoģiski, uz maņu prognozēm balstīti procesi, un kustību veikšanu var saprast kā maņu prognožu piepildīšanu. Izmantojot uztveres analoģiju, pētījumā tiek eksperimentāli pārbaudīts, vai kustību sagatavošanu var saprast kā uzmanību, kas veltīta ķermeņa iekšējo maņu prognozēm.

aktīvā inferencePsiholoģijauzmanībakustību sagatavošana
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Causal Models for Monitoring University Ordinary Financing Fund

2012

Recently iterated decreasing government transfers and an increasing proportion of budget allotted basing on competitive performances, took Italian Universities started struggling with competition for funds, in particular for the University Ordinary Financing Fund (FFO). Aim of this paper is monitoring variables responsible for FFO indicators, where monitoring means: describing, analysing retrospectively, predicting and intervening on variables responsible for indicators. All this aims can be achieved by statistical techniques that should be theoretically equipped with the distinction between predicting under observation and predicting under intervention, in order to provide correct answers …

bayesian inference causal modelling counterfactuals University Ordinary Financing FundSettore SECS-S/01 - Statistica
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贝叶斯因子及其在JASP中的实现

2018

Statistical inference plays a critical role in modern scientific research, however, the dominant method for statistical inference in science, null hypothesis significance testing (NHST), is often misunderstood and misused, which leads to unreproducible findings. To address this issue, researchers propose to adopt the Bayes factor as an alternative to NHST. The Bayes factor is a principled Bayesian tool for model selection and hypothesis testing, and can be interpreted as the strength for both the null hypothesis H0 and the alternative hypothesis H1 based on the current data. Compared to NHST, the Bayes factor has the following advantages: it quantifies the evidence that the data provide for…

business.industryAlternative hypothesisBayesian probabilityBayes factorMachine learningcomputer.software_genreBayesian statisticsFrequentist inferenceStatistical inferenceArtificial intelligenceNull hypothesisbusinessGeneral Economics Econometrics and FinancecomputerStatistical hypothesis testingAdvances in Psychological Science
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