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In the literature, there are algorithms associated with the design of simulations of technological processes, in which the material model has always been defined previously. However, in none of the studies of computer simulation modelling of technological processes known to the authors of this article, is there a detailed description of how the algorithm, or the selection of plastic model used, is...
A model selection algorithm is developed for finding the best model among a set of mixture of normal densities fitted to heterogeneous multivariate data. Model selection algorithm proposed first finds total number of mixture of normal densities then selects possible number of mixture of normal densities and finally searches the best model among them in mixture model clustering of heterogeneous multivariate...
Multi-step ahead forecasting is an important issue for organizations, often used to assist in tactical decisions. Such forecasting can be achieved by adopting time series forecasting methods, such as the classical Holt-Winters (HW) that is quite popular for seasonal series. An alternative forecasting approach comes from the use of more flexible learning algorithms, such as Neural Networks (NN) and...
We present an algorithm called HS-means which is able to learn the number of clusters in a mixture model. Our method extends the concept of clustering stability to a concept of hierarchical stability. The method chooses a model for the data based on analysis of clustering stability; it then analyzes the stability of each component in the estimated model and chooses a stable model for this component...
The natural signal of human such as voice or gesture has been applied to the system for assisting disabled and the elderly people. As an example of such kind of system, the soft remote control system has been developed by HWRS-ERC in KAIST. This system is a vision-based hand gesture recognition system for controlling home appliances such as television, lamp and curtain. One of the most important technologies...
Clustering-based image segment approach is popular in image processing. It consists in separating pixel features into clusters representing homogeneous regions. In the kind of methods, determining the number of clusters is an open problem. In this paper, we propose an efficient model selection algorithm for automatically determining the number of clusters. The algorithm roots the try-and-error approach...
Automatic detection of microcalcifications in mammograms constitutes a helpful tool in breast cancer diagnosis. Radiologist's confidence level on microcalcification detection would be improved if a probability estimate of its presence could be obtained from computer-aided diagnosis. In this paper we explore detection performance of a simple Bayesian classifier based on Gaussian mixture probability...
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