MUMBAI, India, July 13 -- Intellectual Property India has published a patent application (202617076167 A) filed by International Business Machines on June 19, 2026, for Optimization Of Time-Series Anomaly Detection.
Inventors include Han, Si Er; Ma, Xiao Ming; Zhang, Xue Ying Number; Xu, Jing; Yang, Ji Hui; and Wang, Jun.
The application for the patent was published on July 10, 2026, under issue no. 28/2026.
Abstract: An approach to time-series data point anomaly detection may be presented. Data point anomalies in time-series data can cause a cascade of incorrect predictions in a time-series data prediction model. Presented herein may be an approach to decompose a time- series training data set into elementary components, such as seasonal, trend and residual. The approach may determine one or more confidence intervals for elementary components of data points including level shift, variance, and outlier. From these confidence intervals, new data points can be analyzed and identified as anomaly data points. The approach may also prevent anomaly data points from being incorporated into a time series data prediction model, reducing prediction error in the prediction model.
Disclaimer: Curated by HT Syndication.
