Buldakova

A modeling problem of information risks in computer-aided systems was considered in this paper. It was shown that a usage of fuzzy models is a promising approach to solving this problem because their development requires far less information about the system. Analysis of various types of fuzzy models was carried out; their main features were emphasized. The Mamdani model was recognized as the most suitable for estimating information risks. Combination of fuzzy and neural network modeling was proposed; that means the creation of neuro-fuzzy networks by transforming the Mamdani fuzzy model to a self-learning neural network, which operates on the basis of fuzzy logical apparatus and fuzzy sets. An example of a neuro-fuzzy network for an assessment of information risks was presented.

The problem of information security in automated systems is considered in this article. Various approaches to restriction of access to information resources were analyzed. An authorization algorithm was developed; the algorithm uses images which a human will be able to recognize but which an intellectual "program robot" will not be able to recognize. Basic types of distortions of reference images were chosen. It is proposed to apply a dynamic neural network as a peculiar filter allowing one to reject images with high probability of recognition. Hopfield’s recurrent network was used in the implementation of the algorithm.

There are considered the substantive provisions, principles, conditions and mechanisms of realisation in the form of the virtual centre of the new concept in public health services – the personalised medicine. The virtual centre unites all making elements of system of public health services on the basis of the general information field, providing information gathering, the deep analysis and an exchange of great volumes of the data. In this concept the important problem is creation of virtual human physiology. The virtual "copy" of the patient constructed by means of mathematical models of elements and subsystems of an organism, describes activity of physiological subsystems of the person and represents its virtual physiological image. Component of the general virtual model of human physiology is the computer model of biosystem «heart – vessels – lungs». The method of construction of this model on the basis of structurally-parametrical identification and its use for an estimation of a functional state is offered. Transition to the virtual form of the organisation of public health services assumes stage-by-stage realisation of separate projects. A priority problem of the first stage is creation of methods and means of express monitoring and an estimation of a state of health of the person. The prototype of the virtual centre of health protection is offered.

The problem of complex system model reconstruction on incomplete data, in particular, on the experimentally observed signal is considered. Features of wave representation of registered biosignals are investigated. The main stages of creation of the model equations of the complex system which output signals show non-stationary wave character are analyzed. The linear model reconstruction algorithm for the pulse mechanism on the basis of the wave description of a pulse signal is presented. Examples of the basic function choice are given. Comparison with reconstruction algorithms of nonlinear models of complex systems is carried out.

Various problems of prediction in tool production are considered and approaches to their decision are investigated. Features of the accounting of non-stationary production factors and the hidden interrelations are identified. Need of application of artificial neural networks is proved. Algorithms of prediction of equipment loading, need for a material, the forecasting of marriage and energy consumption which are realized by means of a neuronet of direct distribution are offered. Examples of prediction problems in an information and analytical control system of supply and production of the tool are given.