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Mitigação de incertezas atraves da integração com ajuste de historico de produção; Uncertainty mitigation through the integration with production history matching

Gustavo Gabriel Becerra
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 07/12/2007 PT
Relevância na Pesquisa
36.49%
A escassez de informações de qualidade introduz risco ao processo de previsão da produção de petróleo tornando imprescindível o ajuste de histórico de produção, que é a calibração do modelo a partir da resposta produtiva registrada. O ajuste é um problema inverso, em que diferentes combinações dos valores dos parâmetros do reservatório podem conduzir a respostas aceitáveis, especialmente quando o grau de incerteza desses parâmetros é elevado. A integração do ajuste de histórico com a análise probabilística dos cenários representativos conduz à obtenção de uma metodologia para detecção dos modelos calibrados dentro de uma faixa de aceitaçãodefinida. O tratamento de atributos interdependentes de influência global e local e o avanço por etapas são necessários. Desta forma, o objetivo deste trabalho é apresentar uma metodologia que integra a análise de incertezas com o ajuste de histórico em modelos de reservatórios complexos. Este procedimento auxilia a detectar os atributos incertos críticos e sua possível variação com o intuito de estimar a faixa representativa das reservas a desenvolver. Não é alvo obter o melhor ajuste determinístico, mas refletir como o histórico possibilita uma mitigação das incertezas. Assim...

Integração de analise de incertezas e ajuste de historico de produçaõ; Integration of uncertainty analysis and history matching process

Marcos Antonio Bezerra de Moura Filho
Fonte: Biblioteca Digital da Unicamp Publicador: Biblioteca Digital da Unicamp
Tipo: Dissertação de Mestrado Formato: application/pdf
Publicado em 22/02/2006 PT
Relevância na Pesquisa
36.47%
O processo de ajuste de histórico tradicional normalmente resulta em um único modelo determinístico que é utilizado para representar o reservatório, o que pode não ser suficiente para garantir previsões de produção confiáveis, principalmente para campos em início de produção. Este trabalho apresenta uma análise quantitativa das incertezas dos atributos de reservatório integrada com o processo de ajuste de histórico. Ao invés de ser utilizada uma abordagem determinística, aborda-se uma análise probabilística dos modelos de reservatório resultando em faixas de incerteza de previsão de produção e possibilitando uma melhor visão do comportamento futuro de reservatórios. Na metodologia utilizada neste trabalho, dados de simulação são comparados com dados de produção observados e, de acordo com os afastamentos em relação ao histórico de produção, há uma mudança das probabilidades de ocorrência dos cenários. Em alguns procedimentos propostos, há alterações também nos valores dos atributos incertos, diminuindo sua faixa de incerteza. O maior desafio deste trabalho consiste em determinar uma maneira consistente e confiável para promover a integração da análise de incertezas e ajuste de histórico...

Revenue forecast errors in the European Union

Carvalho, Rui Miguel da Costa
Fonte: Instituto Superior de Economia e Gestão Publicador: Instituto Superior de Economia e Gestão
Tipo: Dissertação de Mestrado
Publicado em //2013 ENG
Relevância na Pesquisa
36.23%
Mestrado em Economia Monetária e Financeira; The recent years had brought significant uncertainty to macroeconomic forecasts made not only by specialized international institutions but also by central governments. This dissertation assesses the determinants of revenue forecast errors for the EU-15 between 1999 and 2012, based on the forecasts published bi-annually by the European Commission. A particular important result obtained was that tax rate changes do affect revenue errors and that different tax changes affect differently revenue errors. Also, GDP errors, minority governments, election year and corporate rate changes can be associated to overly optimistic revenue forecasts. On the other hand, 10-year bond yields, inflation errors and VAT changes are associated with a more prudent behaviour.

Impact of weather regimes on the wind power ramp forecast

Couto, A.; Costa, P.; Rodrigues, L.; Lopes, Vitor V.; Estanqueiro, Ana
Fonte: Laboratório Nacional de Energia e Geologia Publicador: Laboratório Nacional de Energia e Geologia
Tipo: Conferência ou Objeto de Conferência
Publicado em //2013 ENG
Relevância na Pesquisa
36.23%
The stochastic nature of wind and the continuous need to balance electric generation with demand poses serious challenges to the power system operators. The impact of large wind integration into the power system is mitigated by decreasing the uncertainty associated with wind forecasts. In particular, the forecast of severe wind power ramps is important due to its impact on the energy market and grid operation and planning. This study proposes to classify the weather regimes over continental Portugal associated with the severe wind power production ramps. Thus, an automated classification system is developed by combining principal components analysis and kmeans clustering to find the most representative atmospheric flow patterns near the surface. This system can tackle with the synoptic spatial variability allowing the decrease of phase and timing mismatches present in single time forecasts. Then, the patterns are linked to the wind power production. Results show that it is possible to associate weather regimes with different levels of wind power production and identify certain atmospheric circulations with a higher chance to trigger severe wind power ramps.

Integrating Forecast Probabilities in Antibiograms: a Way To Guide Antimicrobial Prescriptions More Reliably?

Maurer, Florian P.; Courvalin, Patrice; Böttger, Erik C.; Hombach, Michael
Fonte: American Society for Microbiology Publicador: American Society for Microbiology
Tipo: Artigo de Revista Científica
Publicado em /10/2014 EN
Relevância na Pesquisa
36.12%
Antimicrobial susceptibility testing (AST) assigns pathogens to “susceptible” or “resistant” clinical categories based on clinical breakpoints (CBPs) derived from MICs or inhibition zone diameters and indicates the likelihood for therapeutic success. AST reports do not provide quantitative measures for the reliability of such categorization. Thus, it is currently impossible for clinicians to estimate the technical forecast uncertainty of an AST result regarding clinical categorization. AST error rates depend on the localization of pathogen populations in relation to CBPs. Bacterial species are, however, not homogeneous, and subpopulations behave differently with respect to AST results. We addressed how AST reporting errors differ between isolates with and without acquired drug resistance determinants. Using as an example the beta-lactams and their most important resistance mechanisms, we analyzed different pathogen populations for their individual reporting error probabilities. Categorization error rates were significantly higher for bacterial populations harboring resistance mechanisms than for the wild-type population. Reporting errors for amoxicillin-clavulanic acid and piperacillin-tazobactam in Escherichia coli infection cases were almost exclusively due to the presence of broad-spectrum- and extended-spectrum-beta-lactamase (ESBL)-producing microorganisms (79% and 20% of all errors...

Empirical Simultaneous Confidence Regions for Path-Forecasts

JORDÀ, Òscar; KNÜPPEL, Malte; MARCELLINO, Massimiliano
Fonte: Instituto Universitário Europeu Publicador: Instituto Universitário Europeu
Tipo: Trabalho em Andamento Formato: application/pdf; digital
EN
Relevância na Pesquisa
36.52%
Measuring and displaying uncertainty around path-forecasts, i.e. forecasts made in period T about the expected trajectory of a random variable in periods T+1 to T+H is a key ingredient for decision making under uncertainty. The probabilistic assessment about the set of possible trajectories that the variable may follow over time is summarized by the simultaneous confidence region generated from its forecast generating distribution. However, if the null model is only approximative or altogether unavailable, one cannot derive analytic expressions for this confidence region, and its non-parametric estimation is impractical given commonly available predictive sample sizes. Instead, this paper derives the approximate rectangular confidence regions that control false discovery rate error, which are a function of the predictive sample covariance matrix and the empirical distribution of the Mahalanobis distance of the path-forecast errors. These rectangular regions are simple to construct and appear to work well in a variety of cases explored empirically and by simulation. The proposed techniques are applied to provide con.dence bands around the Fed and Bank of England real-time path-forecasts of growth and inflation.

Ambiguity in ensemble forecasting: evolution, estimate validation and value

Allen, Mark S.
Fonte: Monterey, California: Naval Postgraduate School Publicador: Monterey, California: Naval Postgraduate School
Relevância na Pesquisa
26.6%
Approved for public release, distribution unlimited; An ensemble prediction system (EPS) generates flow-dependent estimates of uncertainty (i.e., random error due to analysis and model errors) associated with a numerical weather prediction model to provide information critical to optimal decision making. Ambiguity, or uncertainty in the prediction of forecast uncertainty, arises due to EPS deficiencies, including finite sampling and inadequate representation of the sources of forecast uncertainty. An EPS based on a low-order dynamical system was used to investigate the behavior of ambiguity, validate two practical estimation methods against a theoretical (impractical) technique, and apply ambiguity in decision making. Ambiguity generally decreased with increasing lead time and was found to depend strongly on ensemble forecast variance and the variability of ensemble mean error. The practical estimation techniques provided reasonably accurate ambiguity estimates, although they were too low at early lead times. The theoretical ambiguity estimate added significant value when combining ambiguity with forecast uncertainty to provide a single normative decision input. Additionally, value added to secondary user criteria (e.g., minimizing repeat false alarms)...

The uncertainty of conditional returns, volatilities and correlations in DCC models

Fresoli, Diego; Ruiz, Esther
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/draft; info:eu-repo/semantics/workingPaper
Publicado em /02/2014 ENG
Relevância na Pesquisa
36.23%
When forecasting conditional correlations that evolve according to a Dynamic Conditional Correlation (DCC) model, only point forecasts can be obtained at each moment of time. In this paper, we analyze the finite sample properties of a bootstrap procedure to approximate the density of these forecasts that also allows obtaining conditional densities for future returns and volatilities. The procedure is illustrated by obtaining conditional forecast intervals and regions of returns, volatilities andcorrelations in the context of a system of daily exchange rates returns of the Euro, Japanese Yen and Australian Dollar against the US Dollar; Both authors acknowledge financial support from the Spanish Government project ECO2012-32401

Model uncertainty and the forecast accuracy of ARMA models: A survey

Gonçalves Mazzeu, Joao Henrique; Ruiz, Esther; Veiga, Helena
Fonte: Universidade Carlos III de Madrid Publicador: Universidade Carlos III de Madrid
Tipo: info:eu-repo/semantics/draft; info:eu-repo/semantics/workingPaper
Publicado em 01/05/2015 ENG
Relevância na Pesquisa
36.54%
The objective of this paper is to survey the literature on the effects of model uncertainty on the forecast accuracy of linear univariate ARMA models. We consider three specific uncertainties: parameter estimation, error distribution and lag order. We also survey the procedures proposed to deal with each of these sources of uncertainty. The results are illustrated with simulated data.; Acknowledgements: Financial support from the Spanish Ministry of Education and Science, research projects ECO2012-32401 and MTM2010-17323 are acknowledged by the three authors and the third author, respectively

A process for applying forecast uncertainty in planning for underway evolutions along intended track

Stoughton, Shane R.
Fonte: Monterey, California. Naval Postgraduate School Publicador: Monterey, California. Naval Postgraduate School
Tipo: Tese de Doutorado Formato: xviii, 155 p. ;
Relevância na Pesquisa
36.23%
Approved for public release; distribution is unlimited; The sensitivity of operational decision making to atmospheric forecasts is a key component of the Decision Tier, or Tier 3, of Battlespace on Demand, Naval Oceanography's operational concept. To that end, effects of different wind forecast inputs were analyzed within a modeled decision context for an aircraft carrier ammunition offload. Development of the decision context using expected distance as the utility measurement was followed by an examination of the climatology of wind events that could adversely affect an offload evolution. Two high-wind event cases from 2009 were chosen for analysis within the decision model. Ensembles from numerical weather prediction models were formed into probabilistic wind forecasts and applied to several decision scenarios. Slight changes to both the forecast inputs and the decision context itself produced different decision outcomes, which emphasized the interdependency between forecasts and optimum decisions in the modeled scenario.; US Navy (USN) author

Extracting value from ensembles for cloud-free forecasting

Stubblefield, Cedrick L.
Fonte: Monterey, California. Naval Postgraduate School Publicador: Monterey, California. Naval Postgraduate School
Formato: xx, 197 p. : ill. ; 28 cm.
Relevância na Pesquisa
36.38%
The Air Force Weather Agency (AFWA) is currently producing cloud-free forecasts for several agencies, but operational forecasts do not incorporate forecast uncertainty. Uncertainty can be forecasted via an ensemble created with perturbed initial conditions. We combine AFWA's global cloud analysis and cloud advection model with the National Centers for Environmental Prediction's global weather ensemble to study the potential for ensemble cloud-free forecasting in support of space-based image collection. A year of ensemble forecasts forms the evaluation dataset. The operationally relevant cloud-free forecast threshold (cloud cover less than 30%) is evaluated over sets of 24-km grid boxes in three climatologically different regions. The analyses and forecasts favor cloud-cover values near 0% and 100% cloud cover, making skill metrics that assume normal statistics mostly inappropriate. Thus we focus on contingency table metrics at the 30% threshold and argue that the odds ratio is most appropriate. Because costs of satellite image collection are largely unknown or classified, and typical cost/loss models may not apply, we also invoke utility theory to quantify operator benefits obtainable from the ensemble. Ensemble skill is apparent, and utility for risk-averse users in persistently clear...

Empirical simultaneous prediction regions for path-forecasts

JORDA, Oscar; KNUEPPEL, Malte; MARCELLINO, Massimiliano
Fonte: Elsevier Science Bv Publicador: Elsevier Science Bv
Tipo: Artigo de Revista Científica
EN
Relevância na Pesquisa
36.29%
This paper investigates the problem of constructing prediction regions for forecast trajectories 1 to H periods into the future a path forecast. When the null model is only approximative, or completely unavailable, one cannot either derive the usual analytic expressions or resample from the null model. In this context, this paper derives a method for constructing approximate rectangular regions for simultaneous probability coverage that correct for serial correlation in the case of elliptical distributions. In both Monte Carlo studies and an empirical application to the Greenbook path-forecasts of growth and inflation, the performance of this method is compared to the performances of the Bonferroni approach and the approach which ignores simultaneity. (C) 2013 International Institute of Forecasters. Published by Elsevier B.V. All rights reserved.

Investment Decision Making Under Deep Uncertainty : Application to Climate Change

Hallegatte, Stéphane; Shah, Ankur; Lempert, Robert; Brown, Casey; Gill, Stuart
Fonte: World Bank, Washington, DC Publicador: World Bank, Washington, DC
Tipo: Publications & Research :: Policy Research Working Paper; Publications & Research
ENGLISH; EN_US
Relevância na Pesquisa
36.29%
While agreeing on the choice of an optimal investment decision is already difficult for any diverse group of actors, priorities, and world views, the presence of deep uncertainties further challenges the decision-making framework by questioning the robustness of all purportedly optimal solutions. This paper summarizes the additional uncertainty that is created by climate change, and reviews the tools that are available to project climate change (including downscaling techniques) and to assess and quantify the corresponding uncertainty. Assuming that climate change and other deep uncertainties cannot be eliminated over the short term (and probably even over the longer term), it then summarizes existing decision-making methodologies that are able to deal with climate-related uncertainty, namely cost-benefit analysis under uncertainty, cost-benefit analysis with real options, robust decision making, and climate informed decision analysis. It also provides examples of applications of these methodologies, highlighting their pros and cons and their domain of applicability. The paper concludes that it is impossible to define the "best" solution or to prescribe any particular methodology in general. Instead...

Hydrologic modeling and uncertainty analysis of an ungauged watershed using mapwindow-swat

Boluwade, Alaba
Fonte: Universidade Nova de Lisboa Publicador: Universidade Nova de Lisboa
Tipo: Dissertação de Mestrado
Publicado em 05/03/2012 ENG
Relevância na Pesquisa
36.15%
Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies; Modeling of an ungauged watershed with the associated uncertainties of the input data is presented. The MapWindow versions of the Soil and Water Assessment Tool (SWAT) have been applied to a complex and ungauged watershed of about 248,000ha in an area close to the Niger River, Nigeria. The Kwara State Government of Nigeria in collaboration with the newly relocated former Zimbabwean farmers now occupied the largest portion of this watershed for an “Agricultural Estate Initiative ”. The government and these farmers are decision makers who need to take appropriate actions despite little or no data availability. SWAT being a physically based model, allow the use of Geographical Information System (GIS) inputs like the Digital Elevation Model(DEM), landuse and soil maps. The MapWindow-SWAT(MSWAT) involves processes like the Watershed Delineation, Hydrological Response Units (HRUs) Process and the SWAT run. The watershed was delineated into 11 subbasins and 28 HRUs. There were 8 landuse classes and 5 soil types. The model was able to simulate and forecast for several years(1990-2016). The results look 'reasonable' since there is no observed data from the watershed for statistical validation. However...

Planeación de ventas y operaciones para EMPACOR S.A.

Paternina Mecías, John Arturo; Duran Millan, Sergio Alejandro; Higuera Baños, Alex Mauricio
Fonte: Facultad de administración Publicador: Facultad de administración
Tipo: info:eu-repo/semantics/bachelorThesis; info:eu-repo/semantics/acceptedVersion Formato: application/pdf
Publicado em 23/09/2011 SPA
Relevância na Pesquisa
36.07%
En el presente trabajo realizado durante el primer semestre de 2011 como estudio basado en la compañía Empacor, buscamos encontrar oportunidades de mejora que permitieran conocer de que manera el uso de una eficiente planeación de ventas y operaciones puede permitirle a una organización compartir información y generar procesos de mejoramiento continuo que le permitan a lo largo de toda la cadena de valor, llevar a cabo procesos efectivos logrando satisfacer al cliente, equilibrando la demanda con el abastecimiento de la organización. Encontramos que a través de un mecanismo utilizado dentro de la organización como son los informes de reclamo se puede visualizar la situación de la compañía y de que manera la observan sus clientes, sin entrar a tener una relación directa con ellos, ya que lo mas importante dentro de cualquier intercambio de bienes y servicios es obtenerlos de la manera que les permita crear una ventaja competitiva y para la organización satisfacer la necesidad y obtener a cambio el valor comercial del producto para de esta manera continuar con su operación.; Centro de Estudios Empresariales para la Perdurabilidad; This work was carried out during the first semester of 2011 as study based on Empacor, Colombian company that is one of the pioneering companies in the production and conversion of paper. Our objective is to find improvement opportunities that allow to know how the correct use of planning together sales and operations can create an organization environment where is possible to share information and generate processes of continuous improvement through all the Supply Chain...

Cost trajectories of low carbon electricity generation technologies: A study of cost uncertainty

Levi, Peter; Pollitt, Michael
Fonte: Elsevier Publicador: Elsevier
Tipo: Article; accepted version
EN
Relevância na Pesquisa
36.23%
This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.enpol.2015.08.003; Cost uncertainty has latterly come to be presented in the UK's Department of Energy and Climate Change (DECC) Levelised Cost of Electricity (LCOE) estimates using sensitivities; 'high' and 'low' figures presented alongside 'central' estimates. This presentation of uncertainty is limited in its provision of context, and as an overall picture of how costs and uncertainty vary over time. This study aims to address these two shortcomings. Two analyses are performed using reported DECC LCOE estimates for three important electricity generation technologies for the UK; nuclear, offshore wind and coal with carbon capture and storage. The first analysis composes LCOE estimate trajectories from previous years' DECC estimates and presents them alongside contextual data, including some out-turn costs. The second quantifies the variability presented in the LCOE estimate trajectories for commissioning dates in the decade 2020-2030. Nuclear costs are presented as both the most consistent and lowest in magnitude. An imminently forecast steep fall in the LCOE of offshore wind raises questions about the timing of investment and deployment. In most cases estimate variability decreases over the estimation horizon...

Assessing forecast uncertainties in a VECX model for Switzerland: an exercise in forecast combination across models and observation windows

Assenmacher-Wesche, Katrin; Pesaran, M. Hashem
Fonte: Faculty of Economics, University of Cambridge, UK Publicador: Faculty of Economics, University of Cambridge, UK
Tipo: Trabalho em Andamento
EN
Relevância na Pesquisa
36.33%
model for Switzerland. Forecast uncertainty is evaluated in three different dimensions. First, we investigate the effect on forecasting performance of averaging over forecasts from different models. Second, we look at different estimation windows. We find that averaging over estimation windows is at least as effective as averaging over different models and both complement each other. Third, we explore whether using weighting schemes from the machine learning literature improves the average forecast. Compared to equal weights the effect of the weighting scheme on forecast accuracy is small in our application.

Can UK passenger vehicles be designed to meet 2020 emissions targets? A novel methodology to forecast fuel consumption with uncertainty analysis.

Martin, Niall P. D.; Bishop, Justin D. K.; Choudhary, Ruchi; Boies, Adam M.
Fonte: Elsevier Publicador: Elsevier
Tipo: Article; published version
EN
Relevância na Pesquisa
36.27%
This is the author accepted mansucript. The final version is available via Elsevier at http://dx.doi.org/10.1016/j.apenergy.2015.03.044; Vehicle manufacturers are required to reduce their European sales-weighted emissions to 95 g CO2/km by 2020, with the aim of reducing on-road fleet fuel consumption. Nevertheless, current fuel consumption models are not suited for the European market and are unable to account for uncertainties when used to forecast passenger vehicle energy-use. Therefore, a new methodology is detailed herein to quantify new car fleet fuel consumption based on vehicle design metrics. The New European Driving Cycle (NEDC) is shown to underestimate on-road fuel consumption in Spark (SI) and Compression Ignition (CI) vehicles by an average of 16% and 13%, respectively. A Bayesian fuel consumption model attributes these discrepancies to differences in rolling, frictional and aerodynamic resistances. Using projected inputs for engine size, vehicle mass, and compression ratio, the likely average 2020 on-road fuel consumption was estimated to be 7.6 L/100 km for SI and 6.4 L/100 km for CI vehicles. These compared to NEDC based estimates of 5.34 L/100 km (SI) and 4.28 L/100 km (CI), both of which exceeded mandatory 2020 fuel equivalent emissions standards by 30.2% and 18.9%...

Uncertainty in the Forecast of Net Load Ramp in CAISO Region

YANG, PEIZHI
Fonte: Universidade Duke Publicador: Universidade Duke
Tipo: Masters' project
Publicado em 23/04/2015 EN_US
Relevância na Pesquisa
56.75%
In electricity systems, demand and supply must be in balance. The term net load refers to the portion of system demand that must be provided by non-renewable resources, equivalent to system demand minus the generation from variable energy resources such as solar and wind. The ramp rate of net load refers to its rate of change. The ramp rate of a power generator refers to the rate at which it can change its generation level. As more intermittent renewable resources are integrated into a system, the ramp rate of net load increases, and with that, the need for flexible generators with higher ramping capability (i.e. the ability to quickly ramp their power output up and down as needed). As more intermittent renewable resources are integrated into a system, the ramp rate of net load increases, and with that, the need for flexible generators with ramping capability. This Masters Project takes data on the forecast and realizations of load and renewable generation in the California Independent System Operator (CAISO) region from 05/01/2014 to 10/31/2014, and examines the statistical properties of the forecast errors of these quantities and the resulting ramp in net load. It focuses on addressing questions regarding the effects of increased penetration of renewables on market and system operations practices: 1) what is the pattern of forecast error of ramp in net load for different daily time periods? 2) Since net load is equal to system demand minus renewable generation...

The many Mexicos: Stochastic forecast 2001-2050

Kesseli,Katja; Galindo,Carlos
Fonte: Universidad Autónoma del Estado de México, Centro de Investigación y Estudios Avanzados de la Población Publicador: Universidad Autónoma del Estado de México, Centro de Investigación y Estudios Avanzados de la Población
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/03/2007 EN
Relevância na Pesquisa
36.29%
Demographic data from Mexico has serious problems of coherence. Most recent estimations are increasing the discrepancies instead of reducing them. Based on analysis of inconsistencies in demographic data, we made a stochastic forecast of Mexican population for the period 2001-2050. The stochastic forecast is composed of random simulations of four different scenarios, which are given by dissimilarities on demographic estimations of the period 1985-2000. This technique allowed us to take into account the uncertainty embedded in Mexican data. Our results imply that is very unlikely (probability 0.07) that Mexican population size in 2005 was lower than 103.2 millions as published in the recent official population count. This result adds up to requests made by other researchers about revisiting and composing consistent demographic estimations.