Analysis of a variable speed vapor compression system using artificial neural networks

Author:

Belman-Flores J.M.,Ledesma S.E.,Garcia M.G.,Ruiz J.,Rodríguez-Muñoz J.L.

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference19 articles.

1. A simulated annealing-based multi-objective optimization algorithm: AMOSA;Bandyopadhyay;IEEE Transactions on Evolutionary Computation,2008

2. Belman, J. M. (2008). Development of a physical model for an installation of production cold by vapour compression using R134a as working fluid. Experimental validation and application for the energetic simulation, Ph.D. Thesis, University Jaume I, Spain [in Spanish].

3. Steady-state model of a variable speed vapor compression system using R134a as working fluid;Belman;International Journal of Energy Research 2009,2009

4. Experimental development of an intelligent refrigeration system;Buzelin;International Journal of Refrigeration,2005

5. Approximation by superpositions of a sigmoidal function;Cybenko;Mathematics of Control Signals and Systems,1989

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