3 results about "Artificial networks" patented technology

The application relates to the field of artificial network control, in particular to an artificial network control method, device and system for shielding across a darkroom. By using a fiber link and an internal battery power supply architecture in a fully-closed shielding darkroom, the interference of personnel on a test environment is completely eliminated, monitoring of parameters such as internal temperature and voltage of the integrated darkroom is added, zero-crossing synchronization noiseless operation of phase switching is realized, in addition, user end environment adaptive identification, driving parameter dynamic calibration and equipment life prediction are realized, and the needs of high-precision, unattended automatic phase switching and testing are met.

This invention relates to the field of artificial power network technology, specifically to a high-voltage artificial power network system and equipment. It includes a DC decoupling network module integrating decoupling capacitors and discharge resistors for power protection; and a DC load network module electrically interconnected with the DC decoupling network module via cables, integrating a multi-stage resistor array, a heat exchanger system, control components, and a cooling subsystem. The cooling subsystem is configured for water-air heat exchange or water-water heat exchange based on the current output stage of the multi-stage resistor array. This invention features efficient heat dissipation and precise temperature control, real-time closed-loop temperature monitoring, and over-temperature alarms for safety. It can promptly observe localized temperature rises and water levels caused by poor cable contact. Connecting to a host computer via a communication module allows for real-time monitoring by the host computer software, and interlocking protection is implemented with the power supply equipment and the tested equipment, simplifying maintenance.

The application discloses a kind of infectious disease network key node identification method based on graph neural network, comprising the following steps: 1, by traditional SIR infectious disease model on the generated network simulates virus transmission process, constructs training data label;2, select the highest score of Kendall coefficient and the score obtained in step 1 is combined with feature, the selected network features are input into the attention model with multiple graph attention layers are introduced, in a variety of artificial networks are trained, to obtain the importance score ranking of each node more suitable;3, consider the "rich club" effect, the obtained ranking sequence is selected by the node selection algorithm based on distance 2-hop, select the node set that the influence range is further expanded.The application provides a new idea and tool for key node identification in complex network, and provides a scientific basis for network optimization and risk prevention.