Aiming at the problems that the existing network flow to QoS (Quality of Service) class aggregation lacks flexibility and the related clustering methods have many iterations and slow clustering, a dynamic flow clustering method was proposed. Using the method of data field clustering and rough set theory, the network flows are clustered according to the QoS attribute value of network flows, and the membership degree of statistics is used to cluster network flows flexibly, so that network flows can be aggregated flexibly. With each data point as the field source, the relationship of each data point in the field is established, and the clustering speed is improved. Experimental results show that the algorithm can play a certain dynamic regulation effect in both low and high load conditions.
In order to improve the detection efficiency and accuracy of spacecraft thermistor wire solder joint detection and defect identification, yolov5 neural network model is studied and optimized, ECA attention module is introduced, infrared thermal imager and microscope lens are used, temperature control fixture and optical fiber coupled semiconductor laser are used to realize the detection of micro holes in its solder joint Infrared image signal acquisition and quality detection of cracks and other defects.
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