By G. Sh. Tsitsiashvili

ISBN-10: 1606920626

ISBN-13: 9781606920626

This booklet offers works on processing time sequence of observations in difficulties of meteorology, ichthyology, clinical geography, epidemiology and demography. those works were released through the authors in the final four years within the Russian journals and suggested at quite a few Russian and overseas meetings. the elemental tools of processing of time sequence within the gathered works are built algorithms for: attractiveness of pictures, classifications, and estimations of dispersions of fluctuations referring to a pattern. the belief of building of the 1st algorithms is composed in learning huge outliers in time sequence. Such strategy has allowed to build very simple for knowing and relatively quickly, as to computing, algorithms of popularity of pictures and classifications and to use them within the difficulties which are characterized by way of huge volumes of empirical information.The 3rd of the desired algorithms is predicated on detailed differences of time sequence to issues of a small pattern and bigger fluctuations. program of conventional algorithms within the thought of arrays of the empirical info calls for complicated calculations. the issues defined in provided works, are real and that is why the utilizing in them of the provided algorithms includes no longer illustrative, yet titanic personality. the issues in query: impact of meteorological elements on severe values: capture of fish(hunchback salmon) within the Amur river, freezing within the Tatar strait, numbers contaminated by way of tick-borne [vernal] encephalitis and different epidemic illnesses in Primorye Territory, impression of financial ameliorations on quite a few age teams of the inhabitants and on dynamics of a inhabitants in towns of the Primorye Territory, effect of worldwide warming on fluctuations of floor temperature in a variety of components of the a long way East.

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Space-Time Prognosis of Tick-Borne Encephalitis Foci Functioning 43 Table 3. The number of people being taken ill with TE for a period of 19731999 in 9 focal areas of Primorsky Krai in absolute and relative indices № Focal district 1. 2. 3. 4. 5. 6. 7. 8. 9. 6 The prognosis of the TE infection rate was performed using PC on the basis of an autoregression model - integrated moving average of Box-Jenkins (ARIMA), one of the most popular models used to process the time series of data and to construct prognoses [1].

Thus, it is believed that the quality of recognition of critical levels of predicted infectious diseases can be improved by way of selection of meteorological data of different weather stations. As a whole, as a result of analysis of Tables 1-4, one can state the very important fact that each of 24 predicted nosologic forms has been recognized, at least, one time with the 100% probability. Let us consider now the results of recognition quality of critical levels of different infectious diseases using the epidemic data as the effecting factors (Table 5).

Sh. Tsitsiashvili Table 4. 4 The results of the second stage of factor temporal prognosis are presented in Table 5. In it, a small fragment of the resulting materials reflecting the accuracy of factor temporal prognosis of critical levels of the TE infection rate realized in real time for different focal districts of Primorsky Krai is given. As the prognostic years, the time series for last 6-8 years were used depending on a character of the long-term dynamics of infection rate typical of one or another focal district.

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Efficient Algorithms of Time Series Processing and Their Applications by G. Sh. Tsitsiashvili

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