Search results for "Prediction."

showing 10 items of 490 documents

Prediction of river discharges at confluences based on Entropy theory and surface-velocity measurements

2022

Hydrodynamic features of the confluence zone of large rivers are complicated because of their three-dimensional flow structure. The confluence between the Rio Negro and the Rio Solimões, characterised by black and white waters, respectively, ranks among the largest river junctions on Earth. An Entropy-based investigation was carried out to assess the discharge and analyse the 2D structure of velocity distribution for large river flows relying on monitoring of near-surface velocity only. The estimated flow data where compared with in-situ ADCP data gathered across some transects of the Negro and Solimões rivers during both low and relatively high flow conditions. Results are illustrated thro…

RiverVelocity-dipconfluenceEntropy methodentropicpredictionMega riverSecondary currentWater Science and Technologyhydrodynamic
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Effects of submerged vegetation on flow and turbulence characteristics at the apex section of a meandering flume

2020

Understanding flow characteristics and turbulent structure in the presence of vegetation is important with respect to environmental processes as sediment transport and mixing of transported quantities. In the present paper attention is focused on the kinematic and turbulent processes in presence of flexible submerged vegetation. In particular, the effect of vegetation on the flux of mass distribution and the process of transport is investigated. The analysis is performed with the aid of detailed experimental data collected in a laboratory channel both in the absence and in presence of flexible and submerged vegetation. Results essentially confirms that mass exchanges in the presence of vege…

Riverpredictionmeander
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Découverte des relations dans les réseaux sociaux

2011

In recent years, social network sites exploded in popularity and become an important part of the online activities on the web. This success is related to the various services/functionalities provided by each site (ranging from media sharing, tagging, blogging, and mainly to online social networking) pushing users to subscribe to several sites and consequently to create several social networks for different purposes and contexts (professional, private, etc.). Nevertheless, current tools and sites provide limited functionalities to organize and identify relationship types within and across social networks which is required in several scenarios such as enforcing users’ privacy, and enhancing t…

Rule-based relationship identificationCoreferent usersMetadataPhotos[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Pas de mot clé en françaisClassificationLink miningSocial networks[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Relationship discoveryLink type predictionEntity resolution[ INFO.INFO-OH ] Computer Science [cs]/Other [cs.OH]CrowdsourcingUser profiles
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A Comprehensive Check of Usle-Based Soil Loss Prediction Models at the Sparacia (South Italy) Site

2020

At first, in this paper a general definition of the event rainfall-runoff erosivity factor for the USLE-based models, REFe = (QR)b1(EI30)b2, in which QR is the event runoff coefficient, EI30 is the single-storm erosion index and b1 and b2 are coefficients, was introduced. The rainfall-runoff erosivity factors of the USLE (b1 = 0, b2 = 1), USLE-M (b1 = b2 = 1), USLE-MB (b1 ≠ 1, b2 = 1), USLE-MR (b1 = 1, b2 ≠ 1), USLE-MM (b1 = b2 ≠ 1) and USLE-M2 (b1 ≠ b2 ≠ 1) can be defined using REFe. Then, the different expressions of REFe were simultaneously tested against a dataset of normalized bare plot soil losses, AeN, collected at the Sparacia (south Italy) site. As expected, the poorest AeN predict…

Runoff coefficientUSLE-type erosion modelsSoil lossSoil loss predictionStatisticsExponentEvent soil loSoil erosionSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliPredictive modellingPlot (graphics)MathematicsEvent (probability theory)
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A Forecasting Support System Based on Exponential Smoothing

2010

This chapter presents a forecasting support system based on the exponential smoothing scheme to forecast time-series data. Exponential smoothing methods are simple to apply, which facilitates computation and considerably reduces data storage requirements. Consequently, they are widely used as forecasting techniques in inventory systems and business planning. After selecting the most adequate model to replicate patterns of the time series under study, the system provides accurate forecasts which can play decisive roles in organizational planning, budgeting and performance monitoring.

Scheme (programming language)Mathematical optimizationSeries (mathematics)Computer sciencebusiness.industryComputationExponential smoothingPrediction intervalReplicatecomputer.software_genreComputer data storageData miningAutoregressive integrated moving averagebusinesscomputercomputer.programming_language
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Contributions to the knowledge base on PV performance: Evaluation of the operation of PV systems using different technologies installed in southern N…

2011

To assist in establishing an accepted knowledge base on PV-modules and systems performance using a representative range of technologies, devices have to be installed at diverse locations, covering a broad range of environmental conditions. For the example of a high latitude location, modules and systems are installed and under investigation in southern Norway (Kristiansand region) by the University of Agder in cooperation with industrial partners. This paper presents first results of the analysis of module performance. The operational behavior of the modules is used to derive a modeling scheme applicable for performance prediction. This use is demonstrated by giving the expected annual perf…

Scheme (programming language)business.industryComputer sciencePhotovoltaic systemElectrical engineeringData modelingKnowledge baseRange (aeronautics)Systems engineeringPerformance predictionOperational behaviorbusinesscomputercomputer.programming_language2011 37th IEEE Photovoltaic Specialists Conference
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Survival Prediction in Intrahepatic Cholangiocarcinoma: A Proof of Concept Study Using Artificial Intelligence for Risk Assessment

2021

Several scoring systems have been devised to objectively predict survival for patients with intrahepatic cholangiocellular carcinoma (ICC) and support treatment stratification, but they have failed external validation. The aim of the present study was to improve prognostication using an artificial intelligence-based approach. We retrospectively identified 417 patients with ICC who were referred to our tertiary care center between 1997 and 2018. Of these, 293 met the inclusion criteria. Established risk factors served as input nodes for an artificial neural network (ANN). We compared the performance of the trained model to the most widely used conventional scoring system, the Fudan score. Pr…

Scoring systemTertiary careArticle03 medical and health sciences0302 clinical medicineintrahepatic cholangiocarcinomaMedicinesurvival predictionIntrahepatic Cholangiocarcinomarisk scoringTraining setFudan scoreArtificial neural networkbusiness.industryRExternal validationGeneral Medicineartificial intelligencemachine learningCholangiocellular carcinoma030220 oncology & carcinogenesisMedicine030211 gastroenterology & hepatologyArtificial intelligencebusinessRisk assessmentartificial neural networkJournal of Clinical Medicine
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Screening for Slow Reading Acquisition in Norway and Finland : a Quest for Context Specific Predictors

2020

Early identification of children at risk of developing reading difficulties is crucial for effective interventions. While orthographies and educational contexts differ, predictors included in early at-risk screening tend to remain rather homogeneous across countries. In this study, we compared longitudinal prediction patterns of being among the 20 percent lowest performing in reading fluency by the end of Grade 1 in Norway (N = 918) and Finland (N =378). The two countries differ in orthographic consistency (semi-transparent versus transparent), age at school entry and pre-primary education. Letter knowledge, phoneme isolation and rapid automatized naming (RAN) were unique predictors in the …

Screening testmedia_common.quotation_subjectEducationDevelopmental psychologyEffective interventionsoppimisvaikeudetPhonological awarenessReading (process):Samfunnsvitenskap: 200::Pedagogiske fag: 280 [VDP]vertaileva tutkimus0501 psychology and cognitive sciencesreading difficultieskielen oppiminenAt-risk studentsmedia_commonFamily characteristics05 social sciences050301 educationennusteetpredictionoikeinkirjoitusIdentification (information)Context specificcross-linguistic comparisonPsychologylukihäiriöt0503 education050104 developmental & child psychologyat-risk students
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A fast and efficient picking algorithm for earthquake early warning application based on the variance piecewise constant models

2020

An earthquake warning system, or earthquake early warning system, is a system of accelerometers, seismometers, communication, computers, and alarms that is devised for notifying adjoining regions of a substantial earthquake while it is in progress. This is not the same as earthquake prediction, which is currently incapable of producing decisive event warnings. The implementation of efficient and computationally simple picking algorithm is necessary for this purpose, as well as automatic picking of seismic phases for seismic surveillance and routine earthquake location for fast hypocenter determination. In this paper a method for picking based on the detection of signals changes in variance …

SeismometerHypocenterWarning systemComputingMethodologies_SIMULATIONANDMODELINGComputer scienceEarthquake predictionEarthquake warning systemVariance (accounting)PickingEarthquake Early WarningPiecewiseChange-pointsSettore SECS-S/01 - StatisticaAlgorithmEarthquake location
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Prior precision modulates the minimisation of prediction error in human auditory cortex

2018

AbstractThe predictive coding model of perception proposes that successful representation of the perceptual world depends upon cancelling out the discrepancy between prediction and sensory input (i.e., prediction error). Recent studies further suggest a distinction between prediction error associated with non-predicted stimuli of different prior precision (i.e., inverse variance). However, it is not fully understood how prediction error from different precision levels is minimised in the predictive process. The current research used magnetoencephalography (MEG) to examine whether prior precision modulates the cortical dynamics of the making of perceptual inferences. We presented participant…

Sensory inputPredictive codingmedicine.diagnostic_testMean squared prediction errorSpeech recognitionPerceptionmedia_common.quotation_subjectmedicineMagnetoencephalographyAuditory cortexMinimisation (clinical trials)Mathematicsmedia_common
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