50 results about "Time series similarity" patented technology

The invention discloses a time series data graphics analysis method based on automatic coding technology with packet loss. The time series data graphics analysis method comprises the following steps: 1) data preprocessing: converting time series data into a specific image format; 2) pre-training: extracting the graphic features of a time series through the automatic coding technology with the packet loss; 3) classifier training: carrying out classifier training to coding machine weight and a training sample class identifier in a pre-training process; and 4) application: realizing the functions of similarity matching and classification of the time series by utilizing the trained classifier. A defect that a traditional time series analysis method is very sensitive to data change since the traditional time series analysis method pays attention to the data feature of the time series is overcome, and a visual processing method of the time series data by people is simulated. On an aspect of the similarity matching, the invention exhibits high accuracy and low time complexity. In classification, high classification precision is guaranteed, and the invention also exhibits good universality and robustness to different types of time series data.

The invention discloses a time sequence similarity query method based on inverted indexes. The method comprises steps of index building and query processing, firstly, a real value type time sequence is converted into a discrete character string through symbol aggregate approximation representation, then a characteristic subsequence is extracted, codes are stored by vector approximation files, the subsequence is converted into word insertion inverted indexes with two types of granularity, and multi-granularity time sequence inverted indexes are built. According to the time sequence similarity query method based on the inverted indexes, an efficient two-stage filtration query method is designed for the indexes, k nearest neighbor similarity query can be realized, on the premise that a higher precision ratio is guaranteed, query time overhead is shorter, and good extendibility for the time sequence length, k nearest neighbor similarity query scale and data set scale is achieved; and the method can play an important role in daily activities and industrial production such as real-time query of stock volatility, on-line pattern recognition of sensor data flow and the like.

The invention provides a similarity time sequence searching method and device. The similarity time sequence searching method and device can realize comparison of macrostates of data and high calculation efficiency. The similarity time sequence searching method comprises the steps that according to a preset state set, target time sequence data of multiple objects are converted into target state sequence data; a state description sequence is matched with the target state sequence data, and under the condition that continuous data in the target state sequence data are matched with all description entries in the state description sequence successfully, the marks of the objects to which the continuous data belong are output.