Title of dissertation: OPTIMIZATION TECHNIQUES FOR ENTROPY-BASED MOMENT MODELS OF LINEAR TRANSPORT Graham West Alldredge, Doctor of Philosophy, 2012 Dissertation directed by: Professor André Tits Department of Electrical and Computer Engineering Kinetic equations are used to model many physical phenomena, including gas dynamics, semiconductors, radiative transport, and more. However, high dimen...

Cycle time optimization could be one of the great challenges in business process management. Although there is much research on this subject, task similarities have been paid little attention. In this paper, a new approach is proposed to optimize cycle time by minimizing entropy of work lists in resource allocation while keeping workloads balanced. The idea of the entropy of work lists comes fr...

Image segmentation is one of the key techniques in the field of image understanding and computer vision. To determine the optimal threshold in image segmentation, an effective image threshold segmentation method based on fuzzy logic is presented. A new kind of fuzzy entropy is defined, that is not only related to the membership, but also related to probability distribution. According to the max...

Multi-objective particle swarm optimization (MOPSO) is a search algorithm based on social behavior. Most of the existing multi-objective particle swarm optimization schemes are based on Pareto optimality and aim to obtain a representative non-dominated Pareto front for a given problem. Several approaches have been proposed to study the convergence and performance of the algorithm, particularly ...

One of the key stages in designing a heat exchanger is optimization process. The enhancement in thermal performance results in a rise in pressure drop and total annual costs. So, finding optimal dimensions of heat exchanger is a key stage in designing process. In this paper, optimization has been done based on entropy generation minimization, where Cuckoo Algorithm aided to reach better results...

The equipment investment scheme evaluation of enterprise is usually multi-objective optimization problem affected by many factors. Among many optimization methods, the common fuzzy matter element is based on the matter-element analysis and combined with the concepts of fuzzy mathematics, which can reflect the subjective fuzzy judgment; the common entropy weight method makes use of the judgment ...

Entropy has been widely employed as an optimization function for problems in computer vision and pattern recognition. To gain insight into such methods it is important to characterize the behavior of the maximum-entropy probability distributions that result from the entropy optimization. The aim of this paper is to establish properties of multivariate distributions maximizing entropy for a gene...

We analyze the performance of the top-down multiclass classification algorithm for decision tree learning called LOMtree, recently proposed in the literature Choromanska and Langford (2014) for solving efficiently classification problems with very large number of classes. The algorithm online optimizes the objective function which simultaneously controls the depth of the tree and its statistica...

In this paper, we investigate a lossy source coding problem, where an upper limit on the permitted distortion is defined for every dataset element. It can be seen as an alternative approach to rate distortion theory where a bound on the allowed average error is specified. In order to find the entropy, which gives a statistical length of source code compatible with a fixed distortion bound, a co...