Documentation corrections and code performance update

[modules/adao.git] / doc / fr / bibliography.rst

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   See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com

   Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D

.. _section_bibliography:

================================================================================
Bibliographie
================================================================================

La présente bibliographie est constituée d'un choix explicite de références à
visée didactique, souvent introductives mais pas uniquement, et dans la mesure
du possible publiquement accessibles. Ces références accompagnent la prise en
main comme l'usage avancé des méthodes disponibles dans le module, sans
néanmoins d'intention de constituer une bibliographie exhaustive.

.. [Argaud09] Argaud J.-P., Bouriquet B., Hunt J., *Data Assimilation from Operational and Industrial Applications to Complex Systems*, Mathematics Today, pp.150-152, October 2009

.. [Asch16] Asch M., Bocquet M., Nodet M., *Data Assimilation - Methods, Algorithms and Applications*, SIAM, 2016

.. [Barrault04] Barrault M., Maday Y., Nguyen N. C., Patera A. T., *An 'empirical interpolation' method: application to efficient reduced-basis discretization of partial differential equations*, Comptes Rendus Mathématique, 339(9), pp.667–672, 2004

.. [Bishop01] Bishop C. H., Etherton B. J., Majumdar S. J., *Adaptive sampling with the ensemble transform Kalman filter. Part I: theoretical aspects*, Monthly Weather Review, 129, pp.420–436, 2001

.. [Bocquet04] Bocquet M., *Introduction aux principes et méthodes de l'assimilation de données en géophysique*, Lecture Notes, 2014

.. [Bouttier99] Bouttier B., Courtier P., *Data assimilation concepts and methods*, Meteorological Training Course Lecture Series, ECMWF, 1999

.. [Buchinsky98] Buchinsky M., *Recent Advances in Quantile Regression Models: A Practical Guidline for Empirical Research*, Journal of Human Resources, 33(1), pp.88-126, 1998

.. [Burgers98] Burgers G., Van Leuween P. J., Evensen G., *Analysis scheme in the Ensemble Kalman Filter*, Monthly Weather Review, 126(6), pp.1719–1724, 1998

.. [Byrd95] Byrd R. H., Lu P., Nocedal J., *A Limited Memory Algorithm for Bound Constrained Optimization*, SIAM Journal on Scientific and Statistical Computing, 16(5), pp.1190-1208, 1995

.. [Cade03] Cade B. S., Noon B. R., *A Gentle Introduction to Quantile Regression for Ecologists*, Frontiers in Ecology and the Environment, 1(8), pp.412-420, 2003

.. [Chakraborty08] Chakraborty U.K., *Advances in differential evolution*, Studies in computational intelligence, Vol.143, Springer, 2008

.. [Chaturantabut10] Chaturantabut S., Sorensen D.C., *Nonlinear model reduction via discrete empirical interpolation*, SIMA Journal of Scientific Computing, 32(5), pp.2737-2764, 2010

.. [Cohn98] Cohn S. E., Da Silva A., Guo J., Sienkiewicz M., Lamich D., *Assessing the effects of data selection with the DAO Physical-space Statistical Analysis System*, Monthly Weather Review, 126, pp.2913–2926, 1998

.. [Courtier94] Courtier P., Thépaut J.-N., Hollingsworth A., *A strategy for operational implementation of 4D-Var, using an incremental approach*, Quarterly Journal of the Royal Meteorological Society, 120(519), pp.1367–1387, 1994

.. [Courtier97] Courtier P., *Dual formulation of four-dimensional variational assimilation*, Quarterly Journal of the Royal Meteorological Society, 123(544), pp.2249-2261, 1997

.. [Das11] Das S., Suganthan P. N., *Differential Evolution: A Survey of the State-of-the-art*, IEEE Transactions on Evolutionary Computation, 15(1), pp.4-31, 2011

.. [Das16] Das S., Mullick S. S., Suganthan P. N., *Recent Advances in Differential Evolution - An Updated Survey*, Swarm and Evolutionary Computation, 27, pp.1-30, 2016

.. [Dautray85] Dautray R., Lions J.-L., et al., *Analyse mathématique et calcul numérique pour les sciences et les techniques*, Tome 1 à 9, Masson, 1985-1988

.. [Evensen94] Evensen G., *Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics*, Journal of Geophysical Research, 99(C5), pp.10143–10162, 1994

.. [Evensen03] Evensen G., *The Ensemble Kalman Filter: theoretical formulation and practical implementation*, Seminar on Recent developments in data assimilation for atmosphere and ocean, ECMWF, 8 to 12 September 2003

.. [GilBellosta15] Gil Bellosta C. J., *rPython: Package Allowing R to Call Python*, CRAN, 2015, https://cran.r-project.org/web/packages/rPython/ and http://rpython.r-forge.r-project.org/

.. [Glover89] Glover F., *Tabu Search-Part I*, ORSA Journal on Computing, 1(2), pp.190-206, 1989

.. [Glover90] Glover F., *Tabu Search-Part II*, ORSA Journal on Computing, 2(1), pp.4-32, 1990

.. [Gnuplot] *Gnuplot - Portable command-line driven graphing utility*, http://www.gnuplot.info/

.. [Gnuplot.py] *Gnuplot.py - A pipe-based interface to the gnuplot plotting program*, http://gnuplot-py.sourceforge.net

.. [Gong18] Gong H., *Data assimilation with reduced basis and noisy measurement: Applications to nuclear reactor cores*, PhD Thesis, Sorbonne Université (France), 2018

.. [Hamill00] Hamill T. M., Snyder C., *A Hybrid Ensemble Kalman Filter-3D Variational Analysis Scheme*, Monthly Weather Review, 128(8), pp.2905-2919, 2000

.. [Ide97] Ide K., Courtier P., Ghil M., Lorenc A. C., *Unified notation for data assimilation: operational, sequential and variational*, Journal of the Meteorological Society of Japan, 75(1B), pp.181-189, 1997

.. [Jazwinski70] Jazwinski A. H., *Stochastic Processes and Filtering Theory*,  Academic Press, 1970

.. [Johnson08] Johnson S. G., *The NLopt nonlinear-optimization package*, http://github.com/stevengj/nlopt

.. [Julier95] Julier S., Uhlmann J., Durrant-Whyte H., *A new approach for filtering nonlinear systems*, in: Proceedings of the 1995 American Control Conference, IEEE, 1995

.. [Julier00] Julier S., Uhlmann J., Durrant-Whyte H., *A new method for the nonlinear transformation of means and covariances in filters and estimators*, IEEE Trans. Automat. Control., 45, pp.477–482, 2000

.. [Julier07] Julier S., Laviola J., *On Kalman filtering with nonlinear equality constraints*, IEEE Trans. Signal Process., 55(6), pp.2774-2784, 2007

.. [Kalnay03] Kalnay E., *Atmospheric Modeling, Data Assimilation and Predictability*, Cambridge University Press, 2003

.. [Koenker00] Koenker R., Hallock K. F., *Quantile Regression: an Introduction*, 2000, http://www.econ.uiuc.edu/~roger/research/intro/intro.html

.. [Koenker01] Koenker R., Hallock K. F., *Quantile Regression*, Journal of Economic Perspectives, 15(4), pp.143-156, 2001

.. [LeDimet86] Le Dimet F.-X., Talagrand 0., *Variational algorithms for analysis and assimilation of meteorological observations*, Tellus, 38A, pp.97-110, 1986

.. [Lions68] Lions J.-L., *Contrôle optimal de systèmes gouvernés par des équations aux dérivées partielles*, Dunod, 1968

.. [Lorenc86] Lorenc A. C., *Analysis methods for numerical weather prediction*, Quarterly Journal of the Royal Meteorological Society, 112(474), pp.1177-1194, 1986

.. [Lorenc88] Lorenc A. C., *Optimal nonlinear objective analysis*, Quarterly Journal of the Royal Meteorological Society, 114(479), pp.205–240, 1988

.. [Morales11] Morales J. L., Nocedal J., *L-BFGS-B: Remark on Algorithm 778: L-BFGS-B, FORTRAN routines for large scale bound constrained optimization*, ACM Transactions on Mathematical Software, 38(1), 2011

.. [Nelder65] Nelder J. A., Mead R., *A simplex method for function minimization*, The Computer Journal, 7, pp.308-313, 1965

.. [NumPy20] Harris C. R. et al., *Array programming with NumPy*, Nature 585, pp.357–362, 2020, https://numpy.org/

.. [Papakonstantinou22] Papakonstantinou K. G., Amir M., Warn G. P., *A Scaled Spherical Simplex Filter (S3F) with a decreased n+2 sigma points set size and equivalent 2n+1 Unscented Kalman Filter (UKF) accuracy*, Mechanical Systems and Signal Processing, 163, 107433, 2022

.. [Powell64] Powell M. J. D., *An efficient method for finding the minimum of a function of several variables without calculating derivatives*, Computer Journal, 7(2), pp.155-162, 1964

.. [Powell94] Powell M. J. D., *A direct search optimization method that models the objective and constraint functions by linear interpolation*, in Advances in Optimization and Numerical Analysis, eds. S. Gomez and J-P Hennart, Kluwer Academic (Dordrecht), pp. 51-67, 1994

.. [Powell98] Powell M. J. D., *Direct search algorithms for optimization calculations*, Acta Numerica 7, pp.287-336, 1998

.. [Powell04] Powell M. J. D., *The NEWUOA software for unconstrained optimization without derivatives*, Proc. 40th Workshop on Large Scale Nonlinear Optimization, Erice, Italy, 2004

.. [Powell07] Powell M. J. D., *A view of algorithms for optimization without derivatives*, Cambridge University Technical Report DAMTP 2007/NA03, 2007

.. [Powell09] Powell M. J. D., *The BOBYQA algorithm for bound constrained optimization without derivatives*, Cambridge University Technical Report DAMTP NA2009/06, 2009

.. [Price05] Price K.V., Storn R., Lampinen J., *Differential evolution: a practical approach to global optimization*, Springer, 2005

.. [Python] *Python programming language*, http://www.python.org/

.. [Quarteroni16] Quarteroni A., Manzoni A., Negri F., *Reduced Basis Methods for Partial Differential Equations - An introduction*, Unitext vol.92, Springer, 2016

.. [R] *The R Project for Statistical Computing*, http://www.r-project.org/

.. [Rowan90] Rowan T., *Functional Stability Analysis of Numerical Algorithms*, Ph.D. thesis, Department of Computer Sciences, University of Texas at Austin, 1990

.. [Salome] *SALOME The Open Source Integration Platform for Numerical Simulation*, http://www.salome-platform.org/

.. [SalomeMeca] *Salome_Meca et Code_Aster, Analyse des Structures et Thermomécanique pour les Etudes et la Recherche*, http://www.code-aster.org/

.. [SciPy20] Virtanen P. et al., *SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python*, Nature Methods, 17(3), pp.261-272, 2020, https://scipy.org/

.. [Storn97] Storn R., Price, K., *Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces*, Journal of Global Optimization, 11(1), pp.341-359, 1997

.. [Tarantola87] Tarantola A., *Inverse Problem: Theory Methods for Data Fitting and Parameter Estimation*, Elsevier, 1987

.. [Talagrand97] Talagrand O., *Assimilation of Observations, an Introduction*, Journal of the Meteorological Society of Japan, 75(1B), pp.191-209, 1997

.. [Tikhonov77] Tikhonov A. N., Arsenin V. Y., *Solution of Ill-posed Problems*, Winston & Sons, 1977

.. [Wan00] Wan E. A., van der Merwe R., *The Unscented Kalman Filter for Nonlinear Estimation*, in: Adaptive Systems for Signal Processing, Communications, and Control Symposium, IEEE, 2000.

.. [Welch06] Welch G., Bishop G., *An Introduction to the Kalman Filter*, University of North Carolina at Chapel Hill, Department of Computer Science, TR 95-041, 2006, http://www.cs.unc.edu/~welch/media/pdf/kalman_intro.pdf

.. [WikipediaDA] Wikipedia, *Data assimilation*, http://en.wikipedia.org/wiki/Data_assimilation

.. [WikipediaKF] Wikipedia, *Kalman Filter*, https://en.wikipedia.org/wiki/Kalman_filter

.. [WikipediaEKF] Wikipedia, *Extended Kalman Filter*, https://en.wikipedia.org/wiki/Extended_Kalman_filter

.. [WikipediaEnKF] Wikipedia, *Ensemble Kalman Filter*, http://en.wikipedia.org/wiki/Ensemble_Kalman_filter

.. [WikipediaMO] Wikipedia, *Mathematical optimization*, https://en.wikipedia.org/wiki/Mathematical_optimization

.. [WikipediaND] Wikipedia, *Nondimensionalization*, https://en.wikipedia.org/wiki/Nondimensionalization

.. [WikipediaNM] Wikipedia, *Nelder–Mead method*, https://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method

.. [WikipediaPSO] Wikipedia, *Particle Swarm Optimization*, https://en.wikipedia.org/wiki/Particle_swarm_optimization

.. [WikipediaQR] Wikipedia, *Quantile regression*, https://en.wikipedia.org/wiki/Quantile_regression

.. [WikipediaTI] Wikipedia, *Tikhonov regularization*, https://en.wikipedia.org/wiki/Tikhonov_regularization

.. [WikipediaTS] Wikipedia, *Tabu search*, https://en.wikipedia.org/wiki/Tabu_search

.. [WikipediaUKF] Wikipedia, *Unscented Kalman Filter*, https://en.wikipedia.org/wiki/Unscented_Kalman_filter

.. [ZambranoBigiarini13] Zambrano-Bigiarini M., Clerc M., Rojas R., *Standard Particle Swarm Optimisation 2011 at CEC-2013: A baseline for future PSO improvements*, 2013 IEEE Congress on Evolutionary Computation, pp.2337-2344, 2013

.. [Zhu97] Zhu C., Byrd R. H., Nocedal J., *L-BFGS-B: Algorithm 778: L-BFGS-B, FORTRAN routines for large scale bound constrained optimization*, ACM Transactions on Mathematical Software, 23(4), pp.550-560, 1997

.. [Zupanski05] Zupanski M., *Maximum likelihood ensemble filter: Theoretical aspects*, Monthly Weather Review, 133(6), pp.1710–1726, 2005

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