2results about How to "Effective strike" patented technology

The present application relates to the field of unmanned aerial vehicle defense, and discloses a method for determining attack sequence of unmanned aerial vehicles, an electronic device and a defense system. The method for determining attack sequence comprises: predicting a first predicted time length when an unmanned aerial vehicle reaches a preset protection boundary, predicting a second predicted time length when the unmanned aerial vehicle reaches a radar detection blind area, determining a target threat level according to the first predicted time length and the second predicted time length, and determining an attack sequence of each unmanned aerial vehicle according to the target threat level of each unmanned aerial vehicle. Therefore, the present embodiment can determine the threat degree of each unmanned aerial vehicle according to the time when each unmanned aerial vehicle will reach the preset protection boundary and the time when each unmanned aerial vehicle will reach the radar detection blind area, and automatically determine the attack sequence according to the threat degree, which is beneficial for a user to aim at each unmanned aerial vehicle according to the attack sequence, shorten the attack decision time, and reduce the attack difficulty, thereby being beneficial for implementing effective attack on each unmanned aerial vehicle in turn before the unmanned aerial vehicles intrude into the preset protection boundary or cross the radar detection blind area.

The application relates to the technical field of behavior data risk determination, and discloses a behavior data risk determination method and device, electronic equipment and a storage medium, wherein the method comprises the following steps: constructing user behavior features in the fusion of time and space dimensions, significantly improving the accuracy of abnormal behavior recognition and reducing the misjudgment rate during the business peak period; using a graph neural network to analyze the correlation between behavior features, generating a risk propagation subgraph and performing risk determination to obtain a risk determination result. The application has the beneficial effects that hidden syndicate fraud networks can be effectively revealed, accurate strikes against collaborative cheating can be realized, the efficiency and accuracy of fraud detection are greatly improved, strategies can be dynamically adjusted according to business scenarios, the normal operation of the business can be ensured while reducing the misjudgment, and a solution is provided for cross-border business anti-fraud.