Design of Cluster Data Association Mining Algorithm Based on Multi-GANs
- Resource Type
- Conference
- Authors
- Qi, Ji; Fu, Weiming
- Source
- 2021 5th International Conference on Computing Methodologies and Communication (ICCMC) Computing Methodologies and Communication (ICCMC), 2021 5th International Conference on. :142-145 Apr, 2021
- Subject
- Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Training
Backpropagation
Neural networks
Clustering algorithms
Encoding
Data mining
Multi-GANs
data mining
cluster computing
neural networks
fuzzy pattern
- Language
Design of general cluster data association mining algorithm based on Multi-GANs is studied in this paper. This article has tested this framework in a variety of environments. Experiments show that the method in this paper can achieve a higher attack success rate for targetless attacks in a white box environment, and it also has a certain attack effect in targeted attacks. The proposed research work considers the GANs, the clustering and the roles of association mining. In the process of error back propagation, the weight and threshold of the network are continuously adjusted to achieve the output that meets the set error. We improve the error coding model to enhance the performance. The experiment results have proven the results.