@inproceedings { , title = {Oil Price Trackers Inspired by Immune Memory}, abstract = {We outline initial concepts for an immune inspired algorithm to evaluate and predict oil price time series data. The proposed solution evolves a short term pool of trackers dynamically, with each member attempting to map trends and anticipate future price movements. Successful trackers feed into a long term memory pool that can generalise across repeating trend patterns. The resulting sequence of trackers, ordered in time, can be used as a forecasting tool. Examination of the pool of evolving trackers also provides valuable insight into the properties of the crude oil market.}, conference = {Proceedings of the Workshop on Artificial Immune Systems and Immune System Modelling (AISB 2006)}, organization = {Bristol, UK}, publicationstatus = {Published}, url = {https://nottingham-repository.worktribe.com/output/1019776}, author = {Wilson, William and Birkin, Phil and Aickelin, Uwe} }