Research on the Fusion Pattern Recognition System Based on the Concept of Production Education Integration and Application of Generative Countermeasure Network

In order to highlight the practical application value of network data and information fusion behavior under the background of industry-education integration, a fusion pattern recognition system that applies generative confrontation network under the concept of industry-education integration is designed. First, the cyclic neural network is used to generate independent text information packets. While establishing the generation of the confrontation network framework, various reinforcement learning parameters are adjusted to realize the construction of the hardware execution environment of the recognition system. On this basis, build an embedded network framework, with the help of EEPROM chip and LD3320 chip circuit, to supervise the fusion process of network data information identification and implementation behavior, and realize the construction of the system’s software execution environment. Combined with the related hardware equipment structure, complete the research on the fusion pattern recognition system of the application generation confrontation network under the concept of integration of production and education. Comparative experiment results show that with the application of the above system, the mean value of network data information fusion time is reduced from 17.9 s to 11.2 s, while the maximum amount of information processed by a single fusion process reaches 9.3 × 1012T which can be used in the context of the integration of production and education Effectively highlight the practical application capabilities of network data information fusion behavior.