Search results for "Bayesian [statistical analysis]"
showing 10 items of 299 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…
Analysis and modeling of wind directions time series
2013
This work aims at studying some aspects of wind directions in Italy and supplying appropriate models. A comparison is presented between independent mixture and Hidden Markov models, which seem to be appropriate as far as the series we studied.
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 …
New Optimization and Security Approaches to Enhance the Smart Grid Performance and Reliability
2016
International audience; Nowadays, the Smart Grid (SG) is becoming smarter thanks to the integration of different information and communication technologies to enhance the reliability and efficiency of the power grid. However, several issues should be met to ensure high SG performance. Among these issues, we cite the problem of electric vehicles (EVs) integration into the SG to avoid electricity intermittence due to the important load that EVs can create. Another issue is the SG communication network security that can be attempted by malicious intruders in order to create damages and make the power grid instable. In this context, we propose at a first level a Bayesian game-theory model that …
Automated uncertainty quantification analysis using a system model and data
2015
International audience; Understanding the sources of, and quantifying the magnitude of, uncertainty can improve decision-making and, thereby, make manufacturing systems more efficient. Achieving this goal requires knowledge in two separate domains: data science and manufacturing. In this paper, we focus on quantifying uncertainty, usually called uncertainty quantification (UQ). More specifically, we propose a methodology to perform UQ automatically using Bayesian networks (BN) constructed from three types of sources: a descriptive system model, physics-based mathematical models, and data. The system model is a high-level model describing the system and its parameters; we develop this model …
A modeling approach to evaluate the influence of spatial and temporal structure of an epidemiological surveillance network on the intensity of phytos…
2017
National audience
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 …
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 …
Implementing ecosystem approach to fishery management: advances and new tools
2013
Desde la antigüedad, la pesca ha sido una fuente importante de alimentos para la humanidad, así como fuente de empleo y beneficios económicos para quienes se dedican a esta actividad. Sin embargo, con el aumento de los conocimientos científicos y la evolución dinámica de la pesca se hizo evidente de que los recursos acuáticos, aunque renovables, no eran infinitos y era necesario gestionar adecuadamente su contribución al bienestar nutricional, económico y el bienestar social de la población mundial para un crecimiento y desarrollo sostenible. En los últimos años, la pesca mundial se ha convertido en un sector dinámico y de desarrollo de la industria alimentaria. Los estados costeros han pro…
Some contributions in disease mapping modeling
2020
Disease mapping ha recibido un gran interés durante las tres últimas décadas. Esta área de investigación persigue el estudio de la distribución geográfica de eventos relacionados con la salud, tales como la mortalidad o la incidencia de enfermedades, agregados en unidades geográficas, con el fin de identificar principalmente aquellas localizaciones que presentan un mayor riesgo. La aplicación de métodos estadísticos avanzados para llevar a cabo las estimaciones de los riesgos resulta fundamental para obtener estimaciones precisas y profundizar en el entendimiento de la distribución geográfica de las enfermedades. En esta tesis nos centramos en la aplicación y evaluación de varias propuestas…