A Network Security Situation Prediction Method Based On SA-SSA

Mathematical programming and meta-heuristics are two types of optimization methods. Meta-heuristic algorithms can identify optimal/near-optimal solutions by mimicking natural behaviours or occurrences and provide benefits such as simplicity of execution, a few parameters, avoidance of local optimization, and flexibility. Many meta-heuristic algorithms have been introduced to solve optimization issues, each of which has advantages and disadvantages. Studies and research on presented meta-heuristic algorithms in prestigious journals showed they had good performance in solving hybrid, improved and mutated problems. This paper reviews the sparrow search algorithm (SSA), one of the new and robust algorithms for solving optimization problems. This paper covers all the SSA literature on variants, improvement, hybridization, and optimization. According to studies, the use of SSA in the mentioned areas has been equal to 32%, 36%, 4%, and 28%, respectively. The highest percentage belongs to Improved, which has been analyzed by three subsections: Meat-Heuristics, artificial neural networks, and Deep Learning.

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A Network Security Situation Prediction Method Based On Attention-CNN-BiGRU

2022

2022 IEEE 25th International Conference on Computer Supported Cooperative Work in Design (CSCWD)

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A Network Security Situation Prediction Method Based On SA-SSA

Cited by 4 publications

References 8 publications

Industrial IoT Network Security Situation Prediction Based on Improved SSA-BiLSTM

Industrial IoT Network Security Situation Prediction Based on Improved SSA-BiLSTM

Advances in Sparrow Search Algorithm: A Comprehensive Survey

A Network Security Situation Prediction Method Based On Attention-CNN-BiGRU

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