Search results for "Predictive model"

showing 10 items of 74 documents

A Neural Network Meta-Model and its Application for Manufacturing

2015

International audience; Manufacturing generates a vast amount of data both from operations and simulation. Extracting appropriate information from this data can provide insights to increase a manufacturer's competitive advantage through improved sustainability, productivity, and flexibility of their operations. Manufacturers, as well as other industries, have successfully applied a promising statistical learning technique, called neural networks (NNs), to extract meaningful information from large data sets, so called big data. However, the application of NN to manufacturing problems remains limited because it involves the specialized skills of a data scientist. This paper introduces an appr…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]0209 industrial biotechnology[SPI] Engineering Sciences [physics]Computer scienceneural networkBig dataContext (language use)02 engineering and technologycomputer.software_genreMachine learningCompetitive advantageData modeling[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SPI]Engineering Sciences [physics]020901 industrial engineering & automationPMML0202 electrical engineering electronic engineering information engineering[ SPI ] Engineering Sciences [physics][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]data analyticsArtificial neural networkbusiness.industrymeta-modelMetamodelingmanufacturingAnalyticsSustainabilityPredictive Model Markup LanguageData analysis020201 artificial intelligence & image processingData miningArtificial intelligencebusinesscomputer
researchProduct

ALTERNATIVE MODELS FOR BUILDING ENERGY PERFORMANCE ASSESSMENT

2020

The research activity carried out during the three years of the PhD course attended, at the Engineering Department of the University of Palermo, was aimed at the identification of an alternative predictive model able to solve the traditional building thermal balance in a simple but reliable way, speeding up any first phase of energy planning. Nowadays, worldwide directives aimed at reducing energy consumptions and environmental impacts have focused the attention of the scientific community on improving energy efficiency in the building sector. The reduction of energy consumption and CO2 emissions for heating and cooling needs of buildings is an important challenge for the European Union, be…

Settore ING-IND/11 - Fisica Tecnica AmbientaleBuilding thermal balance Alternative predictive models MLR Buckingham method ANN Multiple Criteria Assessment LCA
researchProduct

Practical thresholds to distinguish erosive and rill rainfall events

2019

Abstract In this paper, 1017 rainfall events from 2008 to 2017 are used to identify the rainfall threshold that produces upland erosion at the Masse (central Italy) and Sparacia (southern Italy) experimental stations. The rainfall events are classified into three classes: non-erosive, interrill-only and rill. The threshold values for separating as correctly as possible the erosive rains (case I) and the rill rains (case II) are derived solely from the hyetograph. Each threshold value is obtained by imposing that the long-term erosivity of the events above the threshold is equal to the long-term erosivity of all erosive events (case I) or only rill events (case II). The performances of selec…

Water erosionThreshold limit valueRainfall patternSettore AGR/08 - Idraulica Agraria E Sistemazioni Idraulico-ForestaliRUSLEUSLETruncation (statistics)Interrill; Rainfall erosivity; Rainfall hyetograph; Rainfall pattern; Rainfall thresholds; RUSLE; Soil erosion; Soil loss; USLERainfall hyetographWater Science and TechnologyHydrologySoil logeographyRainfall thresholdsgeography.geographical_feature_categoryInterrillRainfall erosivityRainfall thresholdSoil lossRillHyetographSoil erosionErosionEnvironmental scienceScale (map)Predictive modellingJournal of Hydrology
researchProduct

Study on the application of an interspecific competition model for the prediction of microflora behaviour during the fermentation process of S. Angel…

2009

The use of predictive microbiology models able to evaluate bacterial behaviour as a function of environmental conditions and, at the same time, of natural microflora competition was considered by several authors with different approaches. Some authors modelled bacterial competition as a function of metabolic product with particular regard to lactic acid and modelled interspecific bacterial competition introducing a term into a conventional primary predictive model, which gives account for the interaction between two populations, so that they inhibit each other to the same extent that they inhibit their own growth.

Fermentation step; Predictive model; S. Angelo salami; Food safetyGeneral Veterinarybusiness.industryGeneral MedicineInterspecific competitionBiologyFood safetyListeria monocytogenesModels BiologicalSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Biotechnologypredictive modelMeat Productsfood safetyLactobacillusFermentation stepEnterobacteriaceaeFermentationFood MicrobiologyFermentationS. Angelo salamibusinessVeterinary research communications
researchProduct

PMT: New analytical framework for automated evaluation of geo-environmental modelling approaches

2019

Geospatial computation, data transformation to a relevant statistical software, and step-wise quantitative performance assessment can be cumbersome, especially when considering that the entire modelling procedure is repeatedly interrupted by several input/output steps, and the self-consistency and self-adaptive response to the modelled data and the features therein are lost while handling the data from different kinds of working environments. To date, an automated and a comprehensive validation system, which includes both the cutoff-dependent and –independent evaluation criteria for spatial modelling approaches, has not yet been developed for GIS based methodologies. This study, for the fir…

Performance analysiEnvironmental EngineeringGeospatial analysis010504 meteorology & atmospheric sciencesComputer scienceSettore GEO/04 - Geografia Fisica E GeomorfologiaComputationGoodness-of-fit010501 environmental sciencescomputer.software_genre01 natural sciencesRobustness (computer science)ValidationEnvironmental ChemistryWaste Management and Disposal0105 earth and related environmental sciencescomputer.programming_languageEnvironmental modellingReceiver operating characteristicSpatial modellingPerformance analysisLandslidePMTPython (programming language)22/4 OA procedurePollutionDrought riskITC-ISI-JOURNAL-ARTICLEData miningPredictive model evaluation frameworkcomputerScience of The Total Environment
researchProduct

Validation and update of the thoracic surgery scoring system (Thoracoscore) risk model.

2020

Abstract OBJECTIVES The performance of prediction models tends to deteriorate over time. The purpose of this study was to update the Thoracoscore risk prediction model with recent data from the Epithor nationwide thoracic surgery database. METHODS From January 2016 to December 2017, a total of 56 279 patients were operated on for mediastinal, pleural, chest wall or lung disease. We used 3 recommended methods to update the Thoracoscore prediction model and then proceeded to develop a new risk model. Thirty-day hospital mortality included patients who died within the first 30 days of the operation and those who died later during the same hospital stay. RESULTS We compared the baseline patient…

Pulmonary and Respiratory MedicineLung Diseasesmedicine.medical_specialtyCalibration (statistics)030204 cardiovascular system & hematologyOverfittingRisk Assessment03 medical and health sciencesRisk model0302 clinical medicineGoodness of fitRisk FactorsmedicineThoracoscopyHumansHospital MortalityAgedPerformance statusmedicine.diagnostic_testbusiness.industryThoracic SurgeryGeneral MedicineThoracic Surgical Procedures030228 respiratory systemROC CurveCardiothoracic surgeryEmergency medicineSurgeryCardiology and Cardiovascular MedicinebusinessPredictive modellingEuropean journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery
researchProduct

Predictive distribution models of European hake in the south-central Mediterranean Sea

2017

The effective management and conservation of fishery resources requires knowledge of their spatial distribution and notably of their critical life history stages. Predictive modelling of the European hake (Merluccius merluccius L., 1758) distribution was developed in the south-central Mediterranean Sea by means of historical fisheries-independent databases available in the region. The study area included the international waters of the south-central Mediterranean Sea and the territorial waters of Italy, Malta, Tunisia and Libya. Distribution maps of predicted population abundance index, and probabilistic occurrence of recruits and large adults were obtained by means of generalized additive …

0106 biological sciencesMediterranean climateGeneralized additive modelAquatic ScienceSpatial distribution010603 evolutionary biology01 natural sciencesGeneralized additive modelsSeafloor geophysical featureMediterranean seaHakeSeafloor geophysical featuresMerluccius merlucciusSpecies distribution modelling14. Life underwaterLarge adults habitatSettore MAT/07 - Fisica Matematicabiology010604 marine biology & hydrobiologyGeneralized additive modelMerluccius merlucciusbiology.organism_classificationRecruits habitatEnvironmental niche modellingFisheryStrait of SicilyGeographyMerluccius merlucciuPredictive modelling
researchProduct

Predictive models for energy saving in Wireless Sensor Networks

2011

ICT devices nowadays cannot disregard optimizations toward energy sustainability. Wireless Sensor Networks, in particular, are a representative class of a technology where special care must be given to energy saving, due to the typical scarcity and non-renewability of their energy sources, in order to enhance network lifetime. In our work we propose a novel approach that aims to adaptively control the sampling rate of wireless sensor nodes using prediction models, so that environmental phenomena can be consistently modeled while reducing the required amount of transmissions; the approach is tested on data available from a public dataset.

Computer sciencebusiness.industryReliability (computer networking)Distributed computingData modelingKey distribution in wireless sensor networksPredictive ModelWirelessEnergy sourcebusinessWireless sensor networkWireless Sensor NetworkEnergy (signal processing)Predictive modellingEnergy Saving.Computer network2011 IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks
researchProduct

Study of the microstructure and efficiency of YSZ-SPS finely structured ceramic coatings

2018

Thanks to the using of liquid carrier, suspension plasma spray (SPS) enables the manufacture of finely structured coatings. As for conventional plasma spraying (APS), the microstructures of SPS coatings can be tailored by controlling the spray conditions. However, SPS is more complicated than APS due to its number of modifiable parameters.This thesis aims to provide a more fundamental understanding of the relationship between SPS process parameters and the properties of YSZ coatings by identifying generic models based on the use of mathematical statistical methods for the study of influence and sensitivity of the individual parameters.Systematic experiments were carried out to study the inf…

Modèle prédictif[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process EngineeringPredictive modelSuspension plasma sprayProjection plasma de suspensionProcess parameterMultivariate statistics analysisParamètre de procédé[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process EngineeringPorosityMicrostructurePorositéAnalyse statistique multivariée
researchProduct

A Quantum-Inspired Classifier for Early Web Bot Detection

2022

This paper introduces a novel approach, inspired by the principles of Quantum Computing, to address web bot detection in terms of real-time classification of an incoming data stream of HTTP request headers, in order to ensure the shortest decision time with the highest accuracy. The proposed approach exploits the analogy between the intrinsic correlation of two or more particles and the dependence of each HTTP request on the preceding ones. Starting from the a-posteriori probability of each request to belong to a particular class, it is possible to assign a Qubit state representing a combination of the aforementioned probabilities for all available observations of the time series. By levera…

Settore INF/01 - InformaticaComputer Networks and Communicationsbot detectionData modelsTime series analysisearly decisionquantum-inspired computingTime measurementCorrelationCostsmultinomial classificationPredictive modelsbot detection; Correlation; Costs; Data models; early decision; multinomial classification; multivariate sequence classification; Predictive models; quantum-inspired computing; sequential classification; Task analysis; Time measurement; Time series analysis;multivariate sequence classificationTask analysisSafety Risk Reliability and Qualitybot detection; Correlation; Costs; Data models; early decision; multinomial classification; multivariate sequence classification; Predictive models; quantum-inspired computing; sequential classification; Task analysis; Time measurement; Time series analysissequential classification
researchProduct