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PeriodicalsArtificial Intelligence & Machine Learning

A novel bat algorithm fuzzy classifier approach for classification problems

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Abstract & Overview

In this paper, the application of nature-inspired algorithms (NIA) along with fuzzy classifiers is studied. The four algorithms used for the analysis are genetic algorithm, particle swarm optimisation, artificial bee colony and bat algorithm. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results obtained using different fuzzy-NIAs are analysed. Finally, we observe that the fuzzy classifiers under a given set of parameters perform more accurately when applied with the bat algorithm.

Cite this record

Shruti Parashar, J. Senthilnath, Xin‐She Yang (2017). A novel bat algorithm fuzzy classifier approach for classification problems. International Journal of Artificial Intelligence and Soft Computing, 6(2), 108–108. https://doi.org/10.1504/ijaisc.2017.084579

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Parashar, S., Senthilnath, J., & Yang, X. (2017). A novel bat algorithm fuzzy classifier approach for classification problems. International Journal of Artificial Intelligence and Soft Computing, 6(2), 108–108. https://doi.org/10.1504/ijaisc.2017.084579
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