CASPIAN JOURNAL
MANAGEMENT AND HIGH TECHNOLOGIES
, Development of automated system for short-term forecasting of Kyrgyzstan river water content and its testing on the example of the Chu River
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Read | Ten I.G., Musina I.R., Semenenko A.S., Musabaev E.B. , Development of automated system for short-term forecasting of Kyrgyzstan river water content and its testing on the example of the Chu River // Caspian journal : management and high technologies. — 2017. — №4. — pp. 152-165. |
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Ten I.G. - Cand. Sci. (Engineering), Professor, e, Kyrgyz State Technical University named after I. Razzakov, 66 Ch. Aytmatov Ave., Bishkek, 720044, Kyrgyz Republic, iosiften@gmail.com
Musina I.R. - Cand. Sci. (Engineering), Associate Professor, Kyrgyz State Technical University named after I. Razzakov, 66 Ch. Aytmatov Ave., Bishkek, 720044, Kyrgyz Republic, musina-indira@yandex.ru
Semenenko A.S. - Senior Lecturer, Kyrgyz State Technical University named after I. Razzakov, 66 Ch. Aytmatov Ave., Bishkek, 720044, Kyrgyz Republic, anatoliysemenenko@gmail.com
Musabaev E.B. - Senior Lecturer, post-graduate student, Kyrgyz State Technical University named after I. Razzakov, 66 Ch. Aytmatov Ave., Bishkek, 720044, Kyrgyz Republic, emil.musabaev@gmail.com
The aim of this project is to develop an automated forecasting system (AFS) for assessing water content of Kyrgyzstan rivers and its testing on the example of the Chu River, one of the largest rivers in the country. The main factors that influence the forecasting results are the intensity of solar insolation, amount of precipitation, air temperature, and groundwater movement near rivers. The problems that affect the results of hydrological forecasts for mountain rivers are lack of initial observations (due to the inaccessibility of territories and multiple ruggedness of these rivers, changes of the river beds, etc.) and also difficulties in considering all the factors which affect water content in high-mountain conditions. This article proposes to use statistical methods for short-term forecasting of the time series that represent river flow data to obtain predicted values of river water content. The paper justifies practicability of using the forecasting algorithm for structurally changing time series (based on the principle of self-organization) within the AFS development. The functions of the AFS based on this algorithm are described, and the technical requirements for the AFS equipment are grounded. The study is illustrated with the AFS testing results on the example of the Chu River.
Key words: гидроресурсы Кыргызстана, прогнозирование водности рек, краткосрочное прогнози-рование, прогнозирование структурно-изменяющихся временных рядов, алгоритм прогнозирования, предиктор, принцип самоорганизации, требования к системе прогнозирования, автоматизи