This article presents an algorithm for registering the arrival of tsunami waves based on the operational data of sea level measurements. The algorithm was developed using the fuzzy mathematics approach and implies an expert assessment while the procedure of adjustment and tuning. Its adaptive capabilities allow to function in accordance with the current preceding the arrival of a tsunami wave. The presented algorithm tends to be a universal tool that can be used for detecting the restructuring of processes according to measurements of their characteristics in time.

This study addresses the possibility of application of the discrete mathematical analysis (DMA) methods to develop algorithms for registration of tsunami occurrences on the basis of routine data of sea level measurements. The algorithms are based on the relationship between the regression derivative and the trend of the record: areas of positive (negative) derivatives correspond to increasing (decreasing) trends. Boundaries between these areas are extremums. The article describes three DMA-algorithms for tsunami registration, and performs a comparative analysis.

Настоящая статья продолжает цикл работ авторов по разработке математических аспектов методов искусственного интеллекта для обработки наблюдений, проведенных под руководством академика А.Д.Гвишиани, начиная с 2000-го года. Она посвящена новому универсальному методу сглаживания, первоначально предназначенному для анализа геофизических временных рядов. Гравитационные сглаживания легли в основу изучения ускорения векового хода главного магнитного поля Земли на основе данных обсерваторий сети ИНТЕРМАГНЕТ. Но свойства оператора сглаживание до сих пор не были изучены. Данная статья – первый шаг в этом направлении.

The problem of the algorithmic recognition of anomalous time intervals in the time series of the sea-level observations conducted by the Russian Tsunami Warning Survey (RTWS) is considered. The normal and anomalous sea-level observations are described. The polyharmonic models describing the sea-level fluctuations on the short time intervals are constructed, and sea-level forecasting based on these models is suggested. The algorithm for the recognition of anomalous time intervals is developed and its work is tested on the real RTWS data.

Presented are the results of activities on the Russian tsunami warning system updating. Discussed are the design decisions concerning the main components of the service, the seismologic and hydrophysical networks and territorial centers and the structure of the knoware of estimation procedures of tsunami characteristics when making decisions on the tsunami threat and tsunami threat status cancellation.