scholarly journals Towards a General Method for Logical Rule Extraction from Time Series

2019 ◽  
pp. 3-12
Author(s):  
Guido Sciavicco ◽  
Ionel Eduard Stan ◽  
Alessandro Vaccari
Keyword(s):  
Time Series ◽  
Rule Extraction ◽  
Logical Rule ◽  
General Method

Finding the Embedding Dimension and Variable Dependencies in Time Series

1994 ◽  
Vol 6 (3) ◽  
pp. 509-520 ◽  
Author(s):  
Hong Pi ◽  
Carsten Peterson
Keyword(s):  
Time Series ◽  
Time Lag ◽  
Feedforward Neural Networks ◽  
Embedding Dimension ◽  
Conditional Probabilities ◽  
Functional Dependencies ◽  
Sunspot Data ◽  
Synthetic Time Series ◽  
Residual Errors ◽  
General Method

We present a general method, the δ-test, which establishes functional dependencies given a sequence of measurements. The approach is based on calculating conditional probabilities from vector component distances. Imposing the requirement of continuity of the underlying function, the obtained values of the conditional probabilities carry information on the embedding dimension and variable dependencies. The power of the method is illustrated on synthetic time-series with different time-lag dependencies and noise levels and on the sunspot data. The virtue of the method for preprocessing data in the context of feedforward neural networks is demonstrated. Also, its applicability for tracking residual errors in output units is stressed.

scholarly journals POSSIBILITIES OF PERFORMING BANKRUPTCY DATA ANALYSIS USING TIME SERIES CLUSTERING

2010 ◽  
Vol 1 (2) ◽  
pp. 130
Author(s):  
Pēteris Grabusts
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Free Market ◽  
Early Diagnostics ◽  
Time Series Clustering ◽  
Confidence Degree ◽  
Clustering Approach ◽  
Multivariate Discriminant ◽  
The Given ◽  
General Method

Prediction of corporate bankruptcy is a study topic of great interest.Under the conditions of the modern free market, early diagnostics of unfavourabledevelopment trends of company’s activity or bankruptcy becomes a matter ofgreat importance. There is no general method which would allow one to forecastunfavourable consequence with a high confidence degree. This paper focuses onthe analysis of the approaches that can be used to perform an early bankruptcydiagnostics- in previous research multivariate discriminant analysis (MDA), neuralnetwork based approach and rule extraction method have been examined. Lately,time series clustering approach has become popular and its feasibility forbankruptcy data analysis is being investigated. Experiments carried out validatethe use of such methods in the given class of tasks. As a novelty, an attempt toapply time series clustering method to the analysis of bankruptcy data is made.

Fuzzy and Crisp Logical Rule Extraction Methods in Application to Medical Data

2000 ◽  
pp. 593-616 ◽  
Author(s):  
Włodzisław Duch ◽  
Rafał Adamczak ◽  
Krzysztof Grąbczewski ◽  
Grzegorz Żal ◽  
Yoichi Hayashi
Keyword(s):  
Extraction Methods ◽  
Rule Extraction ◽  
Medical Data ◽  
Logical Rule

scholarly journals Towards a More General Method for Filling Gaps in Time Series

2011 ◽  
Vol 7 (S285) ◽  
pp. 392-393
Author(s):  
J. Pascual-Granado ◽  
R. Garrido ◽  
J. Gutirrez-Soto ◽  
S. Martín-Ruiz
Keyword(s):  
Time Series ◽  
Interpolation Method ◽  
Moving Average ◽  
Light Curves ◽  
Arma Models ◽  
Gap Filling ◽  
South Atlantic Anomaly ◽  
Filling Method ◽  
Auto Regressive ◽  
General Method

AbstractThe need for a proper interpolation method for data coming from space missions like CoRoT is emphasized. A new gap-filling method is introduced which is based on auto-regressive moving average interpolation (ARMA) models. The method is tested on light curves from stars observed by the CoRoT satellite, filling the gaps caused by the South Atlantic Anomaly.

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