The cross-entropy method is a versatile heuristic tool for solving difficult estimation and optimization problems, based on Kullback–Leibler (or cross-entropy) minimization. As an optimization method it unifies many existing populationbased optimization heuristics. In this chapter we show how the cross-entropy method can be applied to a diverse range of combinatorial, continuous, and noisy opti...

Several techniques and metrics based on the Second Law of Thermodynamics have been used in the past for the analysis of heat exchangers. The terms used for these techniques include irreversibility analysis, entropy generation minimization, exergy analysis and thermodynamic efficiency. Entransy is a recently developed concept reflecting the heat transfer potential, rather than the ability to con...

in this paper, an enhanced computational code was developed using finite-volume method for solving the incompressible natural convection flow within the cylindrical cavities. grids were generated by an easy method with a view to computer program providing. an explicit integration algorithm was applied to find the steady state condition. also instead of the conventional algorithms of simple, sim...

One way of using the entropy criteria in learning systems is to minimize the entropy of the error between two variables: typically, one is the output of the learning system and the other is the target. This framework has been used for regression. In this paper we show how to use the minimization of the entropy of the error for classification. The minimization of the entropy of the error implies...

One way of using the entropy criteria in learning systems is to minimize the entropy of the error between two variables: typically, one is the output of the learning system and the other is the target. This framework has been used for regression. In this paper we show how to use the minimization of the entropy of the error for classification. The minimization of the entropy of the error implies...