Another proposal is the maximum entropy approach (Pearl 1988, 490 496; Goldszmidt, Morris and Pearl, 1993; Pearl 1990).
The maximum entropy approach is applied to deal with the non-differentiable optimization problems.
This paper also presents an extension of the maximum entropy approach for this kind of devices.
In order to evaluate approximate results for the steady-state probabilities, we employ the maximum entropy approach.
Maximum entropy approach has been applied for an un-reliable server vacation queueing model by Jain et al. (2012).
Similar quantitative considerations play a role in the Maximum Entropy Approach in Goldzsmidt et al. (1993) which is based on ε-semantics.
In this study a maximum entropy approach (Maxent) to forest type classification in a complex Mediterranean area, has been investigated.
The maximum entropy approach (MEP) was introduced by Shannon in (1948) to study the problems of information theory as the measurement of uncertainty.
Further, we intend to determine the approximate results for the steady-state probability distributions of the queue length using the maximum entropy approach.
A Bayesian maximum entropy approach is used for spatial fusion of spatially dispersed estimated one-dimensional models and mapping of the target parameter.
The local maximum entropy approach is easily applicable to the continuum regularization of fluctuating membranes, and the prediction of membrane and bending elasticities of molecular dynamics models.
