M. Albaric, J. Nowag, and P. Papillon, Thermal performance evaluation of solar combisystems using a global approach, 2008.

M. Albaric, B. Mette, J. Ullman, H. Drü-ck, and P. Papillon, Comparison of two different methods for solar combisystems performance testing, EUROSUN, 2010.

. Ansi/ashrae, Method of testing to determine the thermal performance of solar collectors, pp.93-86, 1986.

R. Baccoli, U. Carlini, S. Mariotti, R. Innamorati, E. Solinas et al., Graybox and adaptative dynamic neural network identification models to infer the steady state efficiency of solar thermal collectors starting from the transient condition, Solar Energy, vol.84, pp.1027-1046, 2010.

C. Bales, Combitest -initial development of the AC/DC test method, 2002.

G. Dreyfus, J. Martinez, M. Samuelides, M. B. Gordon, F. Badran et al., Méthodologie et Applications, 2002.

H. Drü-ck and S. Bachmann, Performance testing of solar combisystems. Comparison of the CTSS with the ACDC Procedure, 2002.

E. Standard and E. N. , Thermal solar systems and components -solar collectors -Part 2: Test methods. CEN, Rue de Stassart, vol.36, p.1050, 2006.

, Radiators and convectors -Part 2: Test methods and rating. CEN, Rue de Stassart, European Standard EN, vol.442, issue.2, p.1050, 1996.

R. Heimrath and M. Haller, The reference heating system, the template solar system of Task 32. A report of IEA Solar Heating and Cooling programme -Task 32, International Standar ISO, vol.13790, 2007.

S. A. Kalogirou, Artificial neural networks in renewable energy systems applications: a review, Renewable and Sustainable Energy Reviews, vol.5, pp.373-401, 2001.

S. A. Klein, TRNSYS, A Transient Simulation Program, 1994.

T. Letz, É tude qualitative et quantitative du fonctionnement de Systèmes solaires combines en usage réel. Synthèse du programme de suivi sur sites, 2006.

T. Letz, C. Bales, and B. Perers, A new concept for combisystems characterization: the FSC method, Solar Energy, vol.83, pp.1540-1549, 2009.

D. J. Mackay, A practical Bayesian framework for backpropagation networks, Neural Computation, vol.4, pp.448-472, 1992.

D. W. Marquardt, An algorithm for least-squares estimation of non-linear parameters, Journal of the Society of Industrial and, Applied Mathematics, vol.11, pp.431-441, 1963.

M. Sanino, L. A. Rojas-reischel, and R. A. , Modeling and identification of solar energy water heating system incorporating nonlinearities, Solar Energy, vol.81, pp.570-580, 2007.

A. Mellit and A. Massi-pavan, A 24-h forecast of solar irradiance using artificial neural network: application for performance prediction of a grid-connected PV plant at Trieste, Italy. Solar Energy, vol.84, pp.807-821, 2010.

B. Mette, J. Ullman, H. Drü-ck, M. Albaric, A. Leconte et al., Combisol project. Solar combisystem promotion and standardisation. D3.1: Comparison of test methods, 2010.

D. Nguyen and B. Widrow, Improving the learning speed of 2-layer neural networks by choosing initial values of the adaptative weights, Proceeding of the International Joint Conference on Neural Networks, vol.3, pp.21-26, 1990.

C. Paoli, C. Voyant, M. Museli, and M. L. Nivet, Forecasting of preprocessed daily solar radiation time series using neural networks, Solar Energy, vol.84, pp.2146-2160, 2010.
URL : https://hal.archives-ouvertes.fr/hal-00522627

B. Perers, An improved dynamic solar collector test method for determination of non-linear optical and thermal characteristics with multiple regression, Solar Energy, vol.59, pp.163-178, 1997.

B. Perers and C. Bales, A solar collector model for TRNSYS simulation and system testing, 2002.

, Méthode de calcul Th-CE, Réglementation Thermique RT2005, 2005.

D. E. Rumelhart, G. E. Hinton, and R. J. Williams, Learning representations by back-propagating errors, Nature, vol.323, pp.533-536, 1986.

A. Thü-r, J. Breider, and G. Kuhness, Combisol project. Solar combisystem promotion and standardisation. D2.4: updated state of the art report if solar combisystems analysed within Combisol, 2010.

A. Thü-r, Combisol project. Solar Combisystems promotion and standardisation. D2.3: Guidelines for Design and Dimensioning, 2011.

P. Vogelsanger, The Concise Cycle Test method -A twelve day system test, 2002.

B. Widrow and S. Stearns, Adaptive Signal Processing, 1985.