UAV swarm are often subjected to random interference or malicious attacks during the execution of their tasks, resulting in UAV failure or communication interruption. When the UAV swarm is out of interference or the repair command is executed, the performance of the UAV swarm will be restored to a certain extent. However, how to measure the changes of UAV swarm’s performance during this process will be very important, and it is also crucial to determine whether the UAVs can continue to perform its mission. Based on this motivation, we propose a resilience assessment framework for UAV swarm considering load balancing after UAV swarm suffer from disturbances. We analyze the effects of different topologies and different parameters on the resilience of UAV swarm. The study found that attack intensity is the most important factor affecting UAV swarm performance. As the attack intensity increases, the performance of the UAV swarm decreases rapidly. At the same time, topology also has a very important impact on UAV swarm resilience.

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In recent years, the global temperature is continuously rising and has the trend of accelerating. The frequent occurrence of extremely high temperatures and heat waves has caused widespread concern from all walks of life. How to fully understand the change law of temperature becomes very important. In view of the temperature change in Xi’an, this paper introduces a new method called visibility graph to establish the temperature network in Xi’an. On this basis, firstly, this paper studies the relationship between temperature fluctuation and network degree. We find that short-term fluctuations do not cause long-term effects. Then, through the study of network degree distribution, it is revealed that the temperature network conforms to the law of power-law distribution. In addition, this paper also completes the community detection of temperature network, and finds that some communities have fewer nodes (between June and August), which means that the correlation between summer temperature and other seasons in Xi’an is low, and it is easy to form extreme weather. To sum up, the research in this paper provides a new theoretical method and research ideas for mining and mastering the variation law of temperature in Xi’an.

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