Extended Kalman filter and Takagi-Sugeno fuzzy observer for a strip winding system
This paper proposes two nonlinear estimation approaches, namely based on Extended
Kalman Filter (EKF) and a Takagi-Sugeno Fuzzy Observer with 32 rules (TSFO-32), for a …
Kalman Filter (EKF) and a Takagi-Sugeno Fuzzy Observer with 32 rules (TSFO-32), for a …
Weighted score-driven fuzzy clustering of time series with a financial application
Time series data are commonly clustered based on their distributional characteristics. The
moments play a central role among such characteristics because of their relevant …
moments play a central role among such characteristics because of their relevant …
Knowledge Extraction from PV Power Generation with Deep Learning Autoencoder and Clustering-Based Algorithms
The unpredictable nature of photovoltaic solar power generation, caused by changing
weather conditions, creates challenges for grid operators as they work to balance supply …
weather conditions, creates challenges for grid operators as they work to balance supply …
[HTML][HTML] INGARCH-based fuzzy clustering of count time series with a football application
Although there are many contributions in the time series clustering literature, few studies still
deal with count time series data. This paper aims to develop a fuzzy clustering procedure for …
deal with count time series data. This paper aims to develop a fuzzy clustering procedure for …
Imaging feature-based clustering of financial time series
J Wu, Z Zhang, R Tong, Y Zhou, Z Hu, K Liu - Plos one, 2023 - journals.plos.org
Timeseries representation underpin our ability to understand and predict the change of
natural system. Series are often predicated on our choice of highly redundant factors, and in …
natural system. Series are often predicated on our choice of highly redundant factors, and in …
[HTML][HTML] Hard and soft clustering of categorical time series based on two novel distances with an application to biological sequences
Á López-Oriona, JA Vilar, P D'Urso - Information Sciences, 2023 - Elsevier
Two novel distances between categorical time series are introduced. Both of them measure
discrepancies between extracted features describing the underlying serial dependence …
discrepancies between extracted features describing the underlying serial dependence …
Online risk-based portfolio allocation on subsets of crypto assets applying a prototype-based clustering algorithm
Mean-variance portfolio optimization models are sensitive to uncertainty in risk-return
estimates, which may result in poor out-of-sample performance. In particular, the estimates …
estimates, which may result in poor out-of-sample performance. In particular, the estimates …
Analysis of the cryptocurrency market using different prototype-based clustering techniques
Since the emergence of Bitcoin, cryptocurrencies have grown significantly, not only in terms
of capitalization but also in number. Consequently, the cryptocurrency market can be a …
of capitalization but also in number. Consequently, the cryptocurrency market can be a …
Distance-based one-class time-series classification approach using local cluster balance
Deciding the signal length is an important challenge for one-class time-series classification
(OCTSC). This paper aims to develop an OCTSC algorithm that does not require model …
(OCTSC). This paper aims to develop an OCTSC algorithm that does not require model …
[HTML][HTML] OWA-based robust fuzzy clustering of time series with typicality degrees
In many cases, data are not expressed as individual values on a timeline, but are a
collection of values obtained at certain moments in time-they are time series. In these cases …
collection of values obtained at certain moments in time-they are time series. In these cases …