Visualization of features of a series of measurements with one-dimensional cellular structure
This is an incremental method for researchers analyzing temporal data, such as web publication trends, to identify patterns and anomalies.
The paper tackles the problem of visualizing periodic constituents and instability areas in measurement series by introducing a method based on smoothing algorithms and one-dimensional cellular automata, with an application example in analyzing temporal series of thematic publication volumes in web-space.
This paper describes the method of visualization of periodic constituents and instability areas in series of measurements, being based on the algorithm of smoothing out and concept of one-dimensional cellular automata. A method can be used at the analysis of temporal series, related to the volumes of thematic publications in web-space.