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In the paper the problem of parameter estimation of finite mixture of multivariate Gaussian distributions is considered. A new approach based on differential evolution (DE) algorithm is proposed. In order to avoid problems with infeasibility of chromosomes our version of DE uses a novel representation, in which covariance matrices are encoded using their Cholesky decomposition. Numerical experiments...
As computers are getting faster and disks are growing bigger more data describing user behaviour can be gathered. These data can be analysed to gain insight into user behaviour and then to detect user traits. Currently many different methods are used to analyse data — and there is still no one best method for analysing different parameters of computer systems. Computer systems behave non-linearly...
Travelling salesman problem with profits is a version of a classic travelling salesman problem where it is not necessary to visit all vertices. Instead of it, with each vertex a number meaning a profit is associated. The problem is to find a cycle in a graph which maximizes collected profit but does not exceed a given cost constraint. This problem is NP-hard. Additional assumptions to this problem...
This paper presents a new version of Routes Generation Matrix Algorithm, called Routes Generation Matrix Improved Algorithm (RGMIA), for determining routes with optimal travel time in public transport network. The method was implemented and tested on the real public transport network in Warsaw city. This network was completed with walk links and therefore resultant routes are more practical and can...
The concept of quality of education in education, a number of years ago and is associated with the achievement of agreed standards, as well as consistency between the objectives of the program and the competence of graduates. There is no uniform terminology and definition of ”quality education” is understood as in any field. By E. Deming, ”Quality is what satisfies and even delights the customer”...
Dynamic Bayesian networks (DBNs) offer a framework for explicit modeling of temporal relationships, and are useful as both prognostic and diagnostic tools. In medicine, for example, they can assist in planning treatment options or in clinical management of patients. They have been also widely applied to genomics and proteomics. This paper shows how dynamic Bayesian networks can be used in a risk assessment...
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