[PDF] Top 20 Data-driven model for river flood forecasting based on a Bayesian network approach
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Data-driven model for river flood forecasting based on a Bayesian network approach
... overall model accuracy rate can be estimated as the number of cases where the model correctly predicted the actual discharge value (observation discharges) over all tested cases (here 10,000 ...as a ... Voir le document complet
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Data-driven model for river flood forecasting based on a Bayesian network approach
... the model are continuous, they have to be ...ware-based Bayesian network does not support the introduction of continuous ...discharge data, presented above, in order to identify all ... Voir le document complet
15
Ensemble-based data assimilation for operational flood forecasting – On the merits of state estimation for 1D hydrodynamic forecasting through the example of the “Adour Maritime” river
... hydraulic model terrain is described with 548 topo- graphic and bathymetric cross sections interpolated over 2795 grid ...The river is represented as a 1D flow bounded with infinite banks except in the ... Voir le document complet
16
A Clustering Bayesian Approach for Multivariate Non-Ordered Circular Data
... presents a Bayesian model for the clustering of non-ordered multivariate directional or circular ...our data is that each single observation is made up of k ≥ 2 non-ordered points on ... Voir le document complet
21
A Bayesian approach for clustering and exact finite-sample model selection in longitudinal data mixtures
... having a close form expression for log p(Y, Z|Q) is crucial to adopt such ...to a global optimum. Indeed, CS is a greedy ...with a “clever” initialization of Z, for instance the ... Voir le document complet
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Establishment of Collaborative Networks – A Model-Driven Engineering Approach Based on Thermodynamics
... the network, the risks to be avoided, ...behaviour based on the three other issues assumed to be known, by using different approaches such as model-driven engineering (MDE), optimization, ... Voir le document complet
9
Establishment of collaborative networks – a model-driven engineering approach based on thermodynamics
... presents a theoretical framework to model collaborative networks of organizations according to four dimensions: the context (geographical, social, economical environment), the partners (the actors, their ... Voir le document complet
9
The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification
... chose a recipe dataset 1 for this task because such a dataset requires clusters to be well-explained in order for subjects to be able to perform classification, but does not require special ... Voir le document complet
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A flexible data-driven approach for execution trace filtering
... of data in an execution trace may complexify its ...of a trace, hence the need for a proper filtering ...with a reduced size and complexity, that is easier to analyse. The ... Voir le document complet
7
A distributed parsimonious event-based model for flood forecasting in Mediterranean catchments : efficiency of the model and spatial variability of the parameters
... input data and land-surface parameters, which are in turn derived from various measurements including temperature, precipitation, topography, land uses, soil physical and chemical properties and other hydrological ... Voir le document complet
249
Bayesian Parameterisation of a Regional Photovoltaic Model - Application to Forecasting
... Figure 4: Root mean square difference (RMSD) between the PV model output and the corresponding value obtained with the 22 reference orientation combinations using a multilinear regression. large scale ... Voir le document complet
31
River flood mapping in urban areas combining Radarsat-2 data and flood return period data.
... Areas in shadow and with permanent water surface- like radar response are masked from the final flood map, to reduce over-detections. 82% of pixels correctly detected in urban areas, 2.6% over-detections, 15.6% ... Voir le document complet
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A Data-Driven Regularization Model for Stereo and Flow
... our data-driven smooth- ness term consistently outperforms ...information for some ...in a patch to regular- ize the disparity value at the center ... Voir le document complet
9
Transportation network model with time delay for flood lamination strategy
... cause a sharp increase of the insurance costs, which is no more tolerable in the actual economic ...the river and for which location and sizing are known. A management method computing the ... Voir le document complet
8
A generic data driven approach for low sampling load disaggregation
... using a pattern recognition algorithm [11, ...is a separate device, which has to be installed for training, visualization and communication to the ...at a high sampling rate of all appliances ... Voir le document complet
31
A framework for data-driven design in a product innovation process: data analysis and visualisation for model-based decision making
... of data collection and data communication technologies and the breakthrough of data science algorithms, have created the opportunity to address the lack of data availability in early ...of ... Voir le document complet
28
Metric-Based Model Selection For Time-Series Forecasting
... metric-based model selection (ADJ in particular) to take advantage of (i) the particular structure of time-series data using a transductive inference procedure, and (ii) the difference in ... Voir le document complet
13
A Data-Driven Approach to Modeling Choice
... A Data-Driven Approach to Modeling Choice Vivek ...problem: For a ‘generic’ model of con- sumer choice (namely, distributions over preference lists) and a limited ... Voir le document complet
9
A Model-Driven Approach for Developing a Model Repository: Methodology and Tool Support
... elements. A model can be represented at different levels of abstrac- tion, and the MDE vision is based on (1) the meta-modeling tech- niques to describe these models and (2) the mechanisms to specify ... Voir le document complet
19
Bayesian methods for electricity load forecasting
... of a methodology to improve the estimation and the predictions of a parametric multi-equation model (similar to the one presented in Bruhns et ...over a short ...the model leads to ... Voir le document complet
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