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Title:
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FORECASTING OF THE EMERGENCE AND DEVELOPMENT OF INNOVATIVE TECHNOLOGIES |
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Author(s):
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Andrey V. Proletarsky, Ark M. Andreev, Dmitry V. Berezkin, Ilya A. Kozlov and Moudar Kiwan |
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ISBN:
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978-989-8533-95-1 |
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Editors:
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Hans Weghorn |
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Year:
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2019 |
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Edition:
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Single |
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Keywords:
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Industry 4.0, Situational Analysis, Forecasting, Decision Support System, Scenario Analysis, Clustering |
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Type:
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Short Paper |
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First Page:
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275 |
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Last Page:
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279 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Under Industry 4.0 conditions, the automatic prediction of emergence and evolution of innovative technologies is an
important challenge. To solve this problem, a hybrid approach to big data streams analysis is proposed and developed.
This approach allows the automated monitoring and forecasting of situations development through processing streams of
heterogeneous data which is presented, in particular, by text documents, time series and database records. The proposed
approach includes detecting events in data streams, forming situations, identifying possible scenarios for their further
development and preparing suggestions for decision makers. To represent events that are reflected in a stream of
structured data, a frame-based model is proposed. To form situational chains that reflect the development of innovative
technologies, an incremental clustering method is used. Forecasting further evolution of the analyzed innovative
technology consists in forming possible scenarios for the situations development based on the case-based approach. An
example of an event and a situation detected in a stream of structured data, as well as an example of a scenario generated
for the detected situation are presented. |
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