Information technologies, systems analysis and control

Composite Design Pattern Application and Application of the LINQ Technology in the Context of the Prefix Encoding of Text Using the Huffman Algorithm

The designed methods are the implementation of the object-oriented architecture as the class diagram corresponding to the implementation of the Composite design pattern according to the requirements of the flexible implementation of the Huffman tree, the method of the dynamic iterative Huffman tree building. This tree uses the dynamic collection of the node interface using the Visual C# language and the creation method of the initial set of the leaf nodes using the LINQ technology.

Application of Discrete Structures and Numerical Sequences in Block Codes

The purpose to compress information using composition of universal codes with the recursive algorithm of original data recovery was achieved in this work. It obtains compression coefficient higher than in symbolic coding. Proposed method of time coding has reasonable values of compression coefficient and its purpose is coding with compression. For this purpose, entirely new kind of universal coding with the polybasic numeral system was created.

The Information Technology of Automated Data Processing in the Multi-Channel Ultrasonic Measurement Systems

The article is devoted to the application of information technology for the ultrasonic measurement of linear distances. The most attention is done on improving the accuracy and expansion bands of measurement. For that problem’s solving, using of the multi-channel ultrasonic measuring system that consists a plurality of sensors with various measuring characteristics is proposed.

Improving Adequacy of Type-2 Fuzzy Models by Using Type-2 Fuzzy Sets

An information approach to fuzzy modeling was considered. The present paper formulates the task of developing a formal approach, which would enable analyzing fuzzy systems in terms of their capability to describe uncertainties of input information using interval membership functions. The discussed approach would allow to introduce the information factor for evaluating the quality of fuzzy models functioning using interval membership functions, and to increase the adequacy of the application area representation by a developed fuzzy model.

Estimation of Generalized Linear Models Using Bayesian Approach in Actuarial Modeling

The article deals with Bayesian methodology for estimating unknown parameters of mathematical models and the method of analysis statistic data in insurance based on generalized linear models. These models are extension of linear regression when distribution of random variable can differ from normal. For estimating the parameters of proposed models classical and Bayesian approach were used. The main advantage of Bayesian approach is its ability to generate not only accurate estimates but probability distributions too.

Adjustment of the Iterative Reclassification Method for Including the Rejected Appli-cations into the Credit Scoring

The objective of the research is the adjustment of the Iterative Reclassification Method for including the rejected applications into the credit scoring. The methodology of implementation uses partially classified data and the logistic regression generalization. The method of the adjustment the Weight Of Evidence and the Information Value indicators using the rejected loan applications is proposed at the first stage.

A 2-Layer Perceptron Performance Improvement in Classifying 26 Turned Monochrome 60-by-80-Images Via Training with Pixel-Distorted Turned Images

There is tried 2-layer perceptron in classifying turn-distorted objects at acceptable classification error percentage. The object model is a letter of English alphabet, which is monochrome 60-by-80-image. Neither training 2-layer perceptron with pixel-distorted images, nor with turn-distorted images makes it classify satisfactorily. Therefore in classifying turn-distorted images a 2-layer perceptron performance might be improved via training under distortion modification.

Optimization of Reinsurance Strategies Using DSS

The basic purpose of the work is a study of existing approaches to reinsurance directed towards modeling of distribution and minimization of risk for an insurance portfolio, and forming a strategy for its optimal reinsurance using developed decision support system. A method for a search of optimal reinsurance strategy is proposed. For this purpose statistical models were selected that correspond to the structure and volume of portfolio losses as well as the number of these losses. The simulation model for the total insurance losses is developed.

Optimization Models and Algorithms for Network Problems of Resours’ Distribution

The efficient algorithms for nonlinear programming problems for calculating networks have been offered, as well as the new network models to determine the optimal flows and distribution of resources have been constructed. The problems with nonlinear objective functions of general form and network structure of restrictions, which allow reaching quite a wide range of networks using common approach, were considered. For calculations the modifications of well-known methods of nonlinear programming were applied.

Forecasting Actuarial Processes with Generalized Linear Models

The method for statistical data analysis in insurance based on application of generalized linear models is studied. These models are extension of linear regression when distribution of random variable can differ from normal however belongs to the class of elliptical distributions. The model constructed can be linear or non-linear (for example, logit or probit). For parameters estimation of the models proposed the generalized least squares (GLS) or the Markov chain Monte Carlo methods are used.