Displaying similar documents to “Variational Gaussian process for optimal sensor placement”

A variational model for urban planning with traffic congestion

Guillaume Carlier, Filippo Santambrogio (2010)

ESAIM: Control, Optimisation and Calculus of Variations

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We propose a variational model to describe the optimal distributions of residents and services in an urban area. The functional to be minimized involves an overall transportation cost taking into account congestion effects and two aditional terms which penalize concentration of residents and dispersion of services. We study regularity properties of the minimizers and treat in details some examples.

Variational sensitivity analysis of parametric Markovian market models

Norbert Hilber, Christoph Schwab, Christoph Winter (2008)

Banach Center Publications

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Parameter sensitivities of prices for derivative contracts play an important role in model calibration as well as in quantification of model risk. In this paper a unified approach to the efficient numerical computation of all sensitivities for Markovian market models is presented. Variational approximations of the integro-differential equations corresponding to the infinitesimal generators of the market model differentiated with respect to the model parameters are employed. Superconvergent...

Data-driven penalty calibration: A case study for gaussian mixture model selection

Cathy Maugis, Bertrand Michel (2011)

ESAIM: Probability and Statistics

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In the companion paper [C. Maugis and B. Michel, A non asymptotic penalized criterion for Gaussian mixture model selection. 15 (2011) 41–68] , a penalized likelihood criterion is proposed to select a Gaussian mixture model among a specific model collection. This criterion depends on unknown constants which have to be calibrated in practical situations. A “slope heuristics” method is described and experimented to deal with this practical problem. In a model-based clustering context,...

Ecological-Economic Model of the Region: Information Technology, Forecasting and Optimal Control

V. Gurman, V. Baturin (2009)

Mathematical Modelling of Natural Phenomena

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The paper considers a methodology of mathematical modeling of ecological-economic processes at the regional level. The basis of the model is formed by equations, which describe two interacting blocks: economic and ecological ones. Equations of the economic block are represented by relations of generalized inter-branch balance, while the ecological part is described in terms of differential equations with deviations with respect to some given state of natural resources. Issues of i)...

A rainfall forecasting method using machine learning models and its application to the Fukuoka city case

S. Monira Sumi, M. Faisal Zaman, Hideo Hirose (2012)

International Journal of Applied Mathematics and Computer Science

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In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques. A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid...

A dual data assimilation method for a layered quasi-geostrophic ocean model.

Didier Auroux, Jacques Blum (2002)

RACSAM

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In this paper we introduce the equations of a layered quasi-geostrophic ocean model, and the corresponding data assimilation problem. We first give the variational formulation. We then point out the linear theory of duality. Finally, we apply duality to our nonlinear model by describing an algorithm to solve the data assimilation problem, introducing a dual cost function and a simple way to compute its gradient.