Abstract
A data stream is an ordered sequence of instances that can be read only once or a small number of times using limited computing and storage capabilities. Stream data analysis is a critical issue in many application areas such as network fraud detection, stock market prediction, and web searches. In this research, our previously proposed FCMAC-BYY, that uses Bayesian Ying-Yang (BYY) learning in the fuzzy cerebellar model articulation controller (FCMAC), will be advanced by evolutionary computation and dynamic rule construction. The developed FCMAC-EBYY has been applied to a real-time stream data analysis problem of traffic flow prediction. The experimental results illustrate that FCMAC-EBYY is indeed capable of producing better performance than other representative neuro-fuzzy systems.
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Shi, D., Loomes, M., Nguyen, M.N. (2010). Evolutionary FCMAC-BYY Applied to Stream Data Analysis. In: Deb, K., et al. Simulated Evolution and Learning. SEAL 2010. Lecture Notes in Computer Science, vol 6457. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17298-4_19
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DOI: https://doi.org/10.1007/978-3-642-17298-4_19
Publisher Name: Springer, Berlin, Heidelberg
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