Online Recognition of Fuzzy Time Series Patterns
نویسندگان
چکیده
This article deals with the recognition of recurring multivariate time series patterns modelled sample-point-wise by parametric fuzzy sets. An efficient classification-based approach for the online recognition of incompleted developing patterns in streaming time series is being presented. Furthermore, means are introduced to enable users of the recognition system to restrict results to certain stages of a pattern’s development, e. g. for forecasting purposes, all in a consistently fuzzy manner. Keywords— Fuzzy classification, fuzzy automata, multivariate time series, pattern recognition.
منابع مشابه
A Novel Fuzzy Based Method for Heart Rate Variability Prediction
Abstract In this paper, a novel technique based on fuzzy method is presented for chaotic nonlinear time series prediction. Fuzzy approach with the gradient learning algorithm and methods constitutes the main components of this method. This learning process in this method is similar to conventional gradient descent learning process, except that the input patterns and parameters are stored in mem...
متن کاملShort-Time Prediction Based on Recognition of Fuzzy Time Series Patterns
This article proposes knowledge-based short-time prediction methods for multivariate streaming time series, relying on the early recognition of local patterns. A parametric, well-interpretable model for such patterns is presented, along with an online, classification-based recognition procedure. Subsequently, two options are discussed to predict time series employing the fuzzified pattern knowl...
متن کاملA novel grey–fuzzy–Markov and pattern recognition model for industrial accident forecasting
Industrial forecasting is a top-echelon research domain, which has over the past several years experienced highly provocative research discussions. The scope of this research domain continues to expand due to the continuous knowledge ignition motivated by scholars in the area. So, more intelligent and intellectual contributions on current research issues in the accident domain will potentially ...
متن کاملFuzzy Neural Inference System for Pattern Recognition of Power Quality Events Using Rule Generation
This paper presents pattern recognition of time series data and subsequent temporal data mining of power signal disturbance events that occur frequently in power distribution networks using multiresolution S-transform and Fuzzy neural inference system . This system yields relevant features, which are used in a Fuzzy expert system to separate the transient time series data and steady state short...
متن کاملControl Chart Recognition Patterns using Fuzzy Rule-Based System
Control Chart Patterns (CCPs) recognition is one the most important concepts in control chart application. Relating the patterns exhibited on the control chart to assignable causes is an ambiguous and vague task especially when multiple patterns co-exist. In this study, a fuzzy rule-based system is developed for X ̅ control charts to prioritize the control chart causes based on the accumulated e...
متن کامل