Monitoring of Time Series Using Fuzzy Weighted Prediction Models

Hryniewicz, Olgierd; Kaczmarek-Majer, Katarzyna

doi:10.1007/978-3-319-97547-4_15

Cited by 3 publications

(1 citation statement)

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“…In the recent paper by Kacprzyk et al [14], the authors claim that linguistic data summaries in Yager's sense can be considered an ultimately human consistent form of human-centric aggregation. This paper extends our previous works devoted to the statistical process control that aimed at the monitoring of the autocorrelated health-related processes [10,11,17] and works dedicated to the incorporation of linguistic summaries into time series forecasting [16].…”

Section: Related Worksupporting

confidence: 58%

Personalized linguistic summaries in smartphone-based monitoring of bipolar disorder patients

Kaczmarek-Majer¹,

Hryniewicz²,

Dominiak³

et al. 2019

Proceedings of the 2019 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and

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Personalized linguistic summaries are developed with the use of protoforms in the sense of Yager and Kacprzyk. We discuss the construction and usefulness of such patientdependent and disease-state-dependent linguistic summaries that may be examplied as Most outgoing calls in mania state (disease period) are short compared to the calls recorded in the euthymia state (healthy period). Such linguistic summaries may become important features in the smartphonebased monitoring of the bipolar disorder patients and inform about the detected change in patient's state. The main advantage of the personalized linguistic summaries is their human-centricity. The performance of the proposed approach is illustrated with examples based on the real-life data collected within the observational study.

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