A Two Tiered Cognitive Model for the Forecasting of Time Series Data
نویسندگان
چکیده
This paper describes two mutually enhancing technologies that will be used to evolve Bayesian network based forecasting models;. human/artificial cognition and Bayesian networks. A two tiered representation is introduced which mimics the way the human brain is thought to organize itself. This representation can be manipulated using genetic programming techniques to extract both attributes and organization of a Bayesian Network that models the underlying stochastic process for time series data. Experimental results are presented that demonstrate the effectiveness of the method in forecasting daily prices of stock issues.
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