Abstract
An improved covariance matrix adaptation evolution strategy algorithm (CMA-ES) is proposed and it is used to train the forecasting model of the network security situation in this paper. A new recombination strategy which adds a heuristic component is developed in the improved CMA-ES algorithm, and the search speed is accelerated. The experi- mental results show that, compare with original algorithm and its variants, the improved CMA-ES algorithm can greatly increased the search speed in high dimensional problems. The improved CMA-ES algorithm is an efficient evolutionary algorithm which can be applied to the network security situation prediction.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
