916 resultados para flood forecasting model


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Neste trabalho, foi realizado um estudo de mapeamento de áreas de incidência e previsões para os casos de dengue na área urbana de Belém. Para as previsões foi utilizada à incidência de dengue com a precipitação pluviométrica a partir de modelos estatísticos, baseados na metodologia de Box e Jenkins de series temporais. O período do estudo foi de 05 anos (2007-2011). Na pesquisa temos métodos multivariados de series temporais, com uso de função de transferência e modelos espaciais, em que se analisou a existência de autocorrelações espaciais na variável em estudo. Os resultados das análises dos dados de incidência de casos de dengue e precipitação mostraram que, o aumento no número de casos de dengue acompanha o aumento na precipitação, demonstrando a relação direta entre o número de casos de dengue e a precipitação nos anos em estudo. O modelo de previsão construído para a incidência de casos de dengue apresentou um bom ajuste com resultados satisfatórios podendo, neste caso, ser utilizado na previsão da dengue. Em relação à análise espacial, foi possível uma visualização da incidência de casos na área urbana de Belém, com as respectivas áreas de incidência, mostrando os níveis de significância em porcentagem. Para o período estudado observou-se o comportamento e as variações dos casos de dengue, com destaque para quatro bairros: Marco, Guamá, Pedreira e Tapanã, com possíveis influências destes bairros nas áreas (bairros) vizinhas. Portanto, o presente estudo evidencia a contribuição para o planejamento das ações de controle da dengue, ao servir de instrumento no apoio às decisões na área de saúde pública.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Considering the high competitiveness in the industrial chemical sector, demand forecast is a relevant factor for decision-making. There is a need for tools capable of assisting in the analysis and definition of the forecast. In that sense, the objective is to generate the chemical industry forecast using an advanced forecasting model and thus verify the accuracy of the method. Because it is time series with seasonality, the model of seasonal autoregressive integrated moving average - SARIMA generated reliable forecasts and acceding to the problem analyzed, thus enabling, through validation with real data improvements in the management and decision making of supply chain

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Considering the high competitiveness in the industrial chemical sector, demand forecast is a relevant factor for decision-making. There is a need for tools capable of assisting in the analysis and definition of the forecast. In that sense, the objective is to generate the chemical industry forecast using an advanced forecasting model and thus verify the accuracy of the method. Because it is time series with seasonality, the model of seasonal autoregressive integrated moving average - SARIMA generated reliable forecasts and acceding to the problem analyzed, thus enabling, through validation with real data improvements in the management and decision making of supply chain

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The objective of this work were apply and provide a preliminary evaluation of the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) performance, for Londrina region. We performed comparison with measurements obtained in meteorological stations. The model was configured to run with three domains with 27,9 and 3 km of grid resolution, using the ndown program and also was realized a simulation with the model configured to run with a single domain using a land use file based in a classified image for region of MODIS sensor. The emission files to supply the chemistry run were generated based in the work of Martins et al., 2012. RADM2 chemical mechanism and MADE/SORGAM modal aerosol models were used in the simulations. The results demonstrated that model was able to represent coherently the formation and dispersion of the pollution in Metropolitan Region of Londrina and also the importance of using the appropriate land use file for the region.

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In der hier vorliegenden Arbeit wurde am Beispiel der Kraut- und Knollenfäule an Kartoffeln Phytophthora infestans und des Kartoffelkäfers Leptinotarsa decemlineata untersucht, ob durch den Einsatz von Geographischen Informationssystemen (GIS) landwirtschaftliche Schader¬reger¬prognosen für jeden beliebigen Kartoffelschlag in Deutschland erstellt werden können. Um dieses Ziel zu erreichen, wurden die Eingangsparameter (Temperatur und relative Luftfeuchte) der Prognosemodelle für die beiden Schaderreger (SIMLEP1, SIMPHYT1, SIMPHYT3 and SIMBLIGHT1) so aufbereitet, dass Wetterdaten flächendeckend für Deutschland zur Verfügung standen. Bevor jedoch interpoliert werden konnte, wurde eine Regionalisierung von Deutschland in Interpolationszonen durchgeführt und somit Naturräume geschaffen, die einen Vergleich und eine Bewertung der in ihnen liegenden Wetterstationen zulassen. Hierzu wurden die Boden-Klima-Regionen von SCHULZKE und KAULE (2000) modifiziert, an das Wetterstationsnetz angepasst und mit 5 bis 10 km breiten Pufferzonen an der Grenze der Interpolationszonen versehen, um die Wetterstationen so häufig wie möglich verwenden zu können. Für die Interpolation der Wetterdaten wurde das Verfahren der multiplen Regression gewählt, weil dieses im Vergleich zu anderen Verfahren die geringsten Abweichungen zwischen interpolierten und gemessenen Daten aufwies und den technischen Anforderungen am besten entsprach. Für 99 % aller Werte konnten bei der Temperaturberechnung Abweichungen in einem Bereich zwischen -2,5 und 2,5 °C erzielt werden. Bei der Berechnung der relativen Luftfeuchte wurden Abweichungen zwischen -12 und 10 % relativer Luftfeuchte erreicht. Die Mittelwerte der Abweichungen lagen bei der Temperatur bei 0,1 °C und bei der relativen Luftfeuchte bei -1,8 %. Zur Überprüfung der Trefferquoten der Modelle beim Betrieb mit interpolierten Wetterdaten wurden Felderhebungsdaten aus den Jahren 2000 bis 2007 zum Erstauftreten der Kraut- und Knollenfäule sowie des Kartoffelkäfers verwendet. Dabei konnten mit interpolierten Wetterdaten die gleichen und auch höhere Trefferquoten erreicht werden, als mit der bisherigen Berechnungsmethode. Beispielsweise erzielte die Berechnung des Erstauftretens von P. infestans durch das Modell SIMBLIGHT1 mit interpolierten Wetterdaten im Schnitt drei Tage geringere Abweichungen im Vergleich zu den Berechnungen ohne GIS. Um die Auswirkungen interpretieren zu können, die durch Abweichungen der Temperatur und der relativen Luftfeuchte entstanden wurde zusätzlich eine Sensitivitätsanalyse zur Temperatur und relativen Luftfeuchte der verwendeten Prognosemodelle durchgeführt. Die Temperatur hatte bei allen Modellen nur einen geringen Einfluss auf das Prognoseergebnis. Veränderungen der relativen Luftfeuchte haben sich dagegen deutlich stärker ausgewirkt. So lag bei SIMBLIGHT1 die Abweichung durch eine stündliche Veränderung der relativen Luftfeuchte (± 6 %) bei maximal 27 Tagen, wogegen stündliche Veränderungen der Temperatur (± 2 °C) eine Abweichung von maximal 10 Tagen ausmachten. Die Ergebnisse dieser Arbeit zeigen, dass durch die Verwendung von GIS mindestens die gleichen und auch höhere Trefferquoten bei Schaderregerprognosen erzielt werden als mit der bisherigen Verwendung von Daten einer nahegelegenen Wetterstation. Die Ergebnisse stellen einen wesentlichen Fortschritt für die landwirtschaftlichen Schaderregerprognosen dar. Erstmals ist es möglich, bundesweite Prognosen für jeden beliebigen Kartoffelschlag zur Bekämpfung von Schädlingen in der Landwirtschaft bereit zu stellen.

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L'obiettivo principale della tesi è lo sviluppo di un modello empirico previsivo di breve periodo che sia in grado di offrire previsioni precise ed affidabili dei consumi di energia elettrica su base oraria del mercato italiano. Questo modello riassume le conoscenze acquisite e l'esperienza fatta durante la mia attuale attività lavorativa presso il Romagna Energia S.C.p.A., uno dei maggiori player italiani del mercato energetico. Durante l'ultimo ventennio vi sono stati drastici cambiamenti alla struttura del mercato elettrico in tutto il mondo. Nella maggior parte dei paesi industrializzati il settore dell'energia elettrica ha modificato la sua originale conformazione di monopolio in mercato competitivo liberalizzato, dove i consumatori hanno la libertà di scegliere il proprio fornitore. La modellazione e la previsione della serie storica dei consumi di energia elettrica hanno quindi assunto un ruolo molto importante nel mercato, sia per i policy makers che per gli operatori. Basandosi sulla letteratura già esistente, sfruttando le conoscenze acquisite 'sul campo' ed alcune intuizioni, si è analizzata e sviluppata una struttura modellistica di tipo triangolare, del tutto innovativa in questo ambito di ricerca, suggerita proprio dal meccanismo fisico attraverso il quale l'energia elettrica viene prodotta e consumata nell'arco delle 24 ore. Questo schema triangolare può essere visto come un particolare modello VARMA e possiede una duplice utilità, dal punto di vista interpretativo del fenomeno da una parte, e previsivo dall'altra. Vengono inoltre introdotti nuovi leading indicators legati a fattori meteorologici, con l'intento di migliorare le performance previsive dello stesso. Utilizzando quindi la serie storica dei consumi di energia elettrica italiana, dall'1 Marzo 2010 al 30 Marzo 2012, sono stati stimati i parametri del modello dello schema previsivo proposto e valutati i risultati previsivi per il periodo dall'1 Aprile 2012 al 30 Aprile 2012, confrontandoli con quelli forniti da fonti ufficiali.

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The magnitudes of the largest known floods of the River Rhine in Basel since 1268 were assessed using a hydraulic model drawing on a set of pre-instrumental evidence and daily hydrological measurements from 1808. The pre-instrumental evidence, consisting of flood marks and documentary data describing extreme events with the customary reference to specific landmarks, was “calibrated” by comparing it with the instrumental series for the overlapping period between the two categories of evidence (1808–1900). Summer (JJA) floods were particularly frequent in the century between 1651–1750, when precipitation was also high. Severe winter (DJF) floods have not occurred since the late 19th century despite a significant increase in winter precipitation. Six catastrophic events involving a runoff greater than 6000 m 3 s-1 are documented prior to 1700. They were initiated by spells of torrential rainfall of up to 72 h (1480 event) and preceded by long periods of substantial precipitation that saturated the soils, and/or by abundant snowmelt. All except two (1999 and 2007) of the 43 identified severe events (SEs: defined as having runoff > 5000 and < 6000 m 3 s -1) occurred prior to 1877. Not a single SE is documented from 1877 to 1998. The intermediate 121-year-long “flood disaster gap” is unique over the period since 1268. The effect of river regulations (1714 for the River Kander; 1877 for the River Aare) and the building of reservoirs in the 20th century upon peak runoff were investigated using a one-dimensional hydraulic flood-routing model. Results show that anthropogenic effects only partially account for the “flood disaster gap” suggesting that variations in climate should also be taken into account in explaining these features.

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Esta tesis realiza una contribución metodológica al problema de la gestión óptima de embalses hidroeléctricos durante eventos de avenidas, considerando un enfoque estocástico y multiobjetivo. Para ello se propone una metodología de evaluación de estrategias de laminación en un contexto probabilístico y multiobjetivo. Además se desarrolla un entorno dinámico de laminación en tiempo real con pronósticos que combina un modelo de optimización y algoritmos de simulación. Estas herramientas asisten a los gestores de las presas en la toma de decisión respecto de cuál es la operación más adecuada del embalse. Luego de una detallada revisión de la bibliografía, se observó que los trabajos en el ámbito de la gestión óptima de embalses en avenidas utilizan, en general, un número reducido de series de caudales o hidrogramas para caracterizar los posibles escenarios. Limitando el funcionamiento satisfactorio de un modelo determinado a situaciones hidrológicas similares. Por otra parte, la mayoría de estudios disponibles en este ámbito abordan el problema de la laminación en embalses multipropósito durante la temporada de avenidas, con varios meses de duración. Estas características difieren de la realidad de la gestión de embalses en España. Con los avances computacionales en materia de gestión de información en tiempo real, se observó una tendencia a la implementación de herramientas de operación en tiempo real con pronósticos para determinar la operación a corto plazo (involucrando el control de avenidas). La metodología de evaluación de estrategias propuesta en esta tesis se basa en determinar el comportamiento de éstas frente a un espectro de avenidas características de la solicitación hidrológica. Con ese fin, se combina un sistema de evaluación mediante indicadores y un entorno de generación estocástica de avenidas, obteniéndose un sistema implícitamente estocástico. El sistema de evaluación consta de tres etapas: caracterización, síntesis y comparación, a fin de poder manejar la compleja estructura de datos resultante y realizar la evaluación. En la primera etapa se definen variables de caracterización, vinculadas a los aspectos que se quieren evaluar (seguridad de la presa, control de inundaciones, generación de energía, etc.). Estas variables caracterizan el comportamiento del modelo para un aspecto y evento determinado. En la segunda etapa, la información de estas variables se sintetiza en un conjunto de indicadores, lo más reducido posible. Finalmente, la comparación se lleva a cabo a partir de la comparación de esos indicadores, bien sea mediante la agregación de dichos objetivos en un indicador único, o bien mediante la aplicación del criterio de dominancia de Pareto obteniéndose un conjunto de soluciones aptas. Esta metodología se aplicó para calibrar los parámetros de un modelo de optimización de embalse en laminación y su comparación con otra regla de operación, mediante el enfoque por agregación. Luego se amplió la metodología para evaluar y comparar reglas de operación existentes para el control de avenidas en embalses hidroeléctricos, utilizando el criterio de dominancia. La versatilidad de la metodología permite otras aplicaciones, tales como la determinación de niveles o volúmenes de seguridad, o la selección de las dimensiones del aliviadero entre varias alternativas. Por su parte, el entorno dinámico de laminación al presentar un enfoque combinado de optimización-simulación, permite aprovechar las ventajas de ambos tipos de modelos, facilitando la interacción con los operadores de las presas. Se mejoran los resultados respecto de los obtenidos con una regla de operación reactiva, aun cuando los pronósticos se desvían considerablemente del hidrograma real. Esto contribuye a reducir la tan mencionada brecha entre el desarrollo teórico y la aplicación práctica asociada a los modelos de gestión óptima de embalses. This thesis presents a methodological contribution to address the problem about how to operate a hydropower reservoir during floods in order to achieve an optimal management considering a multiobjective and stochastic approach. A methodology is proposed to assess the flood control strategies in a multiobjective and probabilistic framework. Additionally, a dynamic flood control environ was developed for real-time operation, including forecasts. This dynamic platform combines simulation and optimization models. These tools may assist to dam managers in the decision making process, regarding the most appropriate reservoir operation to be implemented. After a detailed review of the bibliography, it was observed that most of the existing studies in the sphere of flood control reservoir operation consider a reduce number of hydrographs to characterize the reservoir inflows. Consequently, the adequate functioning of a certain strategy may be limited to similar hydrologic scenarios. In the other hand, most of the works in this context tackle the problem of multipurpose flood control operation considering the entire flood season, lasting some months. These considerations differ from the real necessity in the Spanish context. The implementation of real-time reservoir operation is gaining popularity due to computational advances and improvements in real-time data management. The methodology proposed in this thesis for assessing the strategies is based on determining their behavior for a wide range of floods, which are representative of the hydrological forcing of the dam. An evaluation algorithm is combined with a stochastic flood generation system to obtain an implicit stochastic analysis framework. The evaluation system consists in three stages: characterizing, synthesizing and comparing, in order to handle the complex structure of results and, finally, conduct the evaluation process. In the first stage some characterization variables are defined. These variables should be related to the different aspects to be evaluated (such as dam safety, flood protection, hydropower, etc.). Each of these variables characterizes the behavior of a certain operating strategy for a given aspect and event. In the second stage this information is synthesized obtaining a reduced group of indicators or objective functions. Finally, the indicators are compared by means of an aggregated approach or by a dominance criterion approach. In the first case, a single optimum solution may be achieved. However in the second case, a set of good solutions is obtained. This methodology was applied for calibrating the parameters of a flood control model and to compare it with other operating policy, using an aggregated method. After that, the methodology was extent to assess and compared some existing hydropower reservoir flood control operation, considering the Pareto approach. The versatility of the method allows many other applications, such as determining the safety levels, defining the spillways characteristics, among others. The dynamic framework for flood control combines optimization and simulation models, exploiting the advantages of both techniques. This facilitates the interaction between dam operators and the model. Improvements are obtained applying this system when compared with a reactive operating policy, even if the forecasts deviate significantly from the observed hydrograph. This approach contributes to reduce the gap between the theoretical development in the field of reservoir management and its practical applications.

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El presente Proyecto Fin de Carrera consiste en un estudio de los accesos a red que utilizan los servicios a los que están adscritos los usuarios de servicios de teleasistencia, planteando al final del mismo un modelo de previsión de caídas que permita que ese acceso a red no sea un problema para la prestación del servicio. Para poder llegar a los objetivos anteriormente descritos, iniciaremos este documento presentando qué se entiende actualmente como servicios de telemedicina y teleasistencia. Prestaremos atención a los actores que intervienen, usos y beneficios que tienen tanto para los pacientes como para las administraciones públicas. Una vez sepamos en qué consisten, centraremos la atención en las redes de acceso que se utilizan para prestar los servicios de telemedicina, con sus ventajas y desventajas. Puesto que no todos los servicios tienen los mismos requisitos generales de fiabilidad o velocidad de transmisión, veremos cómo se puede garantizar las necesidades de cada tipo de servicio por parte del proveedor de red. El siguiente paso para llegar a establecer el modelo de previsión de caídas será conocer las necesidades técnicas y de los actores para prestar un servicio de teleasistencia en el hogar de un paciente. Esto incluirá estudiar qué equipos se necesitan, cómo gestionarlos y cómo marcar el tráfico para que el operador de red sepa cómo tratarlo según el servicio de teleasistencia que se está utilizando, llevando a generar un modelo de supervisión de enlaces de teleasistencia. Llegados a este punto estaremos ya preparados para establecer un modelo de previsión de caídas de la conexión, describiendo la lógica que se necesite para ello, y poniéndolo en práctica con dos ejemplo concretos: un servicio de telemonitorización domiciliaria y otro servicio de telemonitorización ambulatoria. Para finalizar, realizaremos una recapitulación sobre lo estudiado en este documento y realizaremos una serie de recomendaciones. ABSTRACT. This Thesis is a study of the access network to be used with services assigned to patients that are users of telecare services. In the last chapter we will describe a fall forecasting model that allows the access network to not be an issue for the service. For achieving the objectives described above, this paper will begin with the presentation of what is now understood as telemedicine and telecare services. We pay attention to the actors involved, uses and benefits that they have both for patients and for public administrations. Once we know what telecare means and what requisites they have, we will focus on access networks which are used to provide telemedicine services, with their advantages and disadvantages. Since not all services have the same general requirements of reliability and transmission speed, we will try to see how you can ensure the needs of each type of service from the network provider's point of view. The next step is to establish that the forecasting model of falls will meet the technical needs and actors to provide telecare service in the home of a patient. This will include a study of what equipment is needed, how to manage and how to mark traffic for the network operator knowing how to treat it according to the telecare service being used, and this will lead us to the creation of a model of telecare link monitoring. At this point we are already prepared to establish a forecasting model of connection drops, describing the logic that is needed for this, and putting it into practice with two concrete examples: telemonitoring service and an ambulatory telemonitoring service. Finally, we will have a recap on what has been studied in this paper and will make a series of recommendations.

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In this work, an electricity price forecasting model is developed. The performance of the proposed approach is improved by considering renewable energies (wind power and hydro generation) as explanatory variables. Additionally, the resulting forecasts are obtained as an optimal combination of a set of several univariate and multivariate time series models. The large computational experiment carried out using out-of-sample forecasts for every hour and day allows withdrawing statistically sound conclusions

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While party membership figures are clearly in decline in several Western countries, different interpretations have been offered on the likely consequences of this trend. Some authors stress that members have lost most of their importance for political parties that increasingly rely on professionalized campaign techniques. Other scholars have expressed concern about the decline of party membership. They emphasize the fact that party members continue to function as an important linkage mechanism providing a structural alignment between the party and society (and thus also to potential voters). By means of an election forecasting model for Belgium, we test whether party membership figures still can be related to election results. Results show that party membership has a strong effect on election results, and furthermore, that this relation does not weaken during the period under investigation (1981-2010). The analysis also demonstrates that forecasting models can also be used in a complex multiparty system like Belgium.

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While party membership figures are clearly in decline in several Western countries, different interpretations have been offered on the likely consequences of this trend. Some authors stress that members have lost most of their importance for political parties that increasingly rely on professionalized campaign techniques. Other scholars have expressed concern about the decline of party membership. They emphasize the fact that party members continue to function as an important linkage mechanism providing a structural alignment between the party and society (and thus also to potential voters). By means of an election forecasting model for Belgium, we test whether party membership figures still can be related to election results. Results show that party membership has a strong effect on election results, and furthermore, that this relation does not weaken during the period under investigation (1981-2010). The analysis also demonstrates that forecasting models can also be used in a complex multiparty system like Belgium.

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Shipping list no.: 91-580-P.

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Cover title.