The Study of Time Series Using the DMA Methods and Geophysical Applications
Author(s) -
S. M. Agayan,
Shamil Bogoutdinov,
Anatoly Soloviev,
Роман Сидоров
Publication year - 2016
Publication title -
data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.358
H-Index - 21
ISSN - 1683-1470
DOI - 10.5334/dsj-2016-016
Subject(s) - computer science , class (philosophy) , scope (computer science) , series (stratigraphy) , span (engineering) , cluster analysis , interpreter , fuzzy logic , tracing , algorithm , theoretical computer science , data mining , artificial intelligence , programming language , paleontology , civil engineering , engineering , biology
The discrete mathematical analysis (DMA) is a series of algorithms aimed at the solution of basic problems of data analysis: clustering and tracing in multidimensional arrays, morphological analysis of reliefs, search for anomalies and trends in records etc. All the DMA algorithms are of universal nature, joined by the same formal foundation, based, in its turn, on fuzzy logic (FL) and fuzzy mathematics (FM). The current study finalizes the search for the anomalies in one-dimensional time series within the scope of DMA: here the initial concept of an interpreter’s logic gets its additional development. First, the formal expert’s opinions are more fully expressed, and this is realized with the more complex measures of activity (the concept of straightenings (Gvishiani et al. 2003; Gvishiani et al. 2004; Zlotnicki et al. 2005) is replaced by the measures of activity which come to the fore): second, for the junction of anomalies, a recently created DPS (Discrete Perfect Sets) algorithm is used DPS (Discrete Perfect Sets) (Agayan et al. 2011; Agayan et al. 2014)
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