The monograph is devoted to an investigation of co-operative effects in stochastic models. It includes original results of the authors in the last decade. The main object of the monograph is an analysis of an influence of a stochastic model structure on its characteristics. Problems of a co-operation and a decomposition are actual in a solution of a lot of concrete problems. These problems are: a parallelisation of algorithms and programs, a modelling of supercomputers, computer networks, systems of mobile telephones catastrophes in complex systems, a design and an improvement of technological and economical processes etc. The co-operative effects create a source of significant dependencies between complex system characteristics under large random disturbances. To analyse these effects is necessary to create special methods based on structural analysis of multi-element stochastic models together with majoral asymptotic bounds of these models characteristics. At the same time it demands to develop new approaches to a processing of statistical data and a skill in an usage of the probability theory limit theorems and related asymptotic series and bounds. A choice of the monograph material is defined as by initial applied problems so by probability methods of their solution. Conditionally the monograph may be divided into two parts. First of them contains four sections devoted to a finding of the co-operative effects and to a development of new related analytical and numerical methods. This part has presumably methodological character and creates a theoretical base of an investigation of applied stochastic systems. Second part contains three sections devoted to a solution of different applied problems. It has some interesting substantial results.

This monograph presents important research results in the areas of queuing theory, risk theory, graph theory and reliability theory. The analysed stochastic network models are aggregated systems of elements in random environments. To construct and to analyse a large number of different stochastic network models it is possible by a proof of new analytical results and a construction of calculation algorithms besides of the application of cumbersome traditional techniques Such a constructive approach is in a prior detailed investigation of an algebraic model component and leads to an appearance of new original stochastic network models, algorithms and application to computer science and information technologies. Accuracy and asymptotic formulas, additional calculation algorithms have been constructed due to an introduction of control parameters into analysed models, a reduction of multi-dimensional problems to one dimensional problems, a comparative analysis, a graphic interpretation of network models, an investigation of new models characteristics, a choice of special distributions classes or principles of subsystems aggregation, proves of new statements.

This book presents works on processing time series of observations in problems of meteorology, ichthyology, medical geography, epidemiology and demography. These works have been published by the authors within the last 4 years in the Russian journals and reported at various Russian and international conferences. The basic methods of processing of time series in the collected works are developed algorithms for: recognition of images, classifications, estimations of dispersions of fluctuations concerning a trend. The idea of construction of the first two algorithms consists in studying large outliers in time series. Such approach has allowed to construct quite simple for understanding and rather fast, as to computing, algorithms of recognition of images and classifications and to apply them in the problems that are characterised by large volumes of empirical information. The third of the specified algorithms is based on special transformations of time series to problems with a small trend and greater fluctuations. Application of traditional algorithms in the considered arrays of the empirical information demands complex calculations. The problems described in presented works, are actual and that's why the using in them of the offered algorithms carries not illustrative, but substantial character. The problems in question: influence of meteorological factors on critical values: catch of fish(hunchback salmon) in the Amur river, freezing in the Tatar strait, numbers infected by tick-borne [vernal] encephalitis and other epidemic diseases in Primorye Territory, influence of economic transformations on various age groups of the population and on dynamics of a population in cities of the Primorye Territory, influence of global warming on fluctuations of surface temperature in various areas of the Far East.