This inventor holds 1 USPTO granted patent. Top assignee: Nortel Networks Corporation. Active years: 2004.
Company Filing History:
Years Active: 2004
Title: Jason Levesley: Innovator in Data Prediction Technologies
Introduction
Jason Levesley is a notable inventor based in Southbank, GB. He has made significant contributions to the field of data prediction, particularly in communications networks. His innovative approach utilizes techniques adapted from chaos theory to analyze and predict future values of data series.
Latest Patents
Levesley holds a patent for a method of predicting values of a series of communications data. This patent focuses on analyzing traffic levels in a communications network. By determining an attractor structure from the communications data, his invention allows for the monitoring, controlling, and analyzing of communications processes. The results from this prediction can be used to modify the communications process, ultimately reducing costs and improving performance and efficiency. His methods can also be applied to product data from manufacturing processes. An algorithm bank is compiled containing various prediction algorithms suitable for different types of data series, including both deterministic and stochastic behaviors. The assessment of recent past values of a data series is conducted in real time to select the optimal prediction algorithm, ensuring accurate forecasting even as data series change over time.
Career Highlights
Levesley is associated with Nortel Networks Corporation, where he has been able to apply his innovative ideas in a practical setting. His work has contributed to advancements in the efficiency of communications networks.
Collaborations
Some of his notable coworkers include Malcolm Edward Carter and Otakar Fojt, who have collaborated with him on various projects.
Conclusion
Jason Levesley is a pioneering inventor whose work in data prediction technologies has the potential to transform communications networks and manufacturing processes. His innovative methods and algorithms are paving the way for more efficient data management and analysis.