Abstract
To realize that the false positive rate and false negative rate can be adjusted and improve the detection accuracy of the classical Dendritic Cell Algorithm which contains various uncertain elements, the concept of Tendency Factor and a Result-Controllable Dendritic Cell Algorithm are proposed by analyzing the signal processing function, weight matrixes and the other random parameters involved. The new algorithm has the higher detection accuracy and better robustness, in which the Tendency Factor can be obtained according to different contexts in order to control the detection results. Simulation experiments are performed using different parameters and multiple data sets and the Tendency Factor and the Result-Controllable Dendritic Cell Algorithm are proved to be reasonable and effective.
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Yuan, S., Zhang, H. (2014). Result-Controllable Dendritic Cell Algorithm. In: Huang, DS., Bevilacqua, V., Premaratne, P. (eds) Intelligent Computing Theory. ICIC 2014. Lecture Notes in Computer Science, vol 8588. Springer, Cham. https://doi.org/10.1007/978-3-319-09333-8_21
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DOI: https://doi.org/10.1007/978-3-319-09333-8_21
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-09332-1
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