基于量子密码的卫星网络地球站异常检测系统设计

传统的卫星网络地球站异常检测系统设计在检测过程中稳定性差,异常频率识别能力低。为了解决上述问题,基于量子密码研究了一种新的卫星网络地球站异常检测系统,系统硬件主要由感应器、异常分析器、警示器、数据采集器、数据解析器、预处理器六部分组成,感应器负责感应卫星网络地球站的各方面的数据监测系统是否正常,异常分析器可以分析感应器感应到的数据是否存在异常,警示器能够通过界面向工作人员发出警示信号,数据采集器负责采集信息,由数据解析器解析采集到的信息,预处理器实现信息处理。通过数据采集应用程序、异常检测应用程序、数据处理应用程序实现系统工作。为验证系统运行有效性,设定对比实验,结果表明,相较于传统系统,基于量子密码的卫星网络地球站异常检测系统稳定性提高了15.2%,异常频率识别能力提高了19.8%。

Simulation Research on Mine Collapse Risk Assessment Model

The mine is affected by the external environment and internal factors. It is very likely that there will be landslides, and the degree of landslide will be different, and the impact will be different. The mine landslide risk assessment model currently studied has poor ability to collect data, and it is impossible to study the data in completeness. It is difficult to achieve dynamic assessment, and the decision-making scheme obtained is not scientific enough. Aiming at the above problems, based on the traditional mine collapse risk assessment model, a new model is designed to determine the factor finding principle of mine collapse risk index system, and the indicators are standardized, according to the identified proportion of mine collapse risk indicators. The grading function, after the game, selects the appropriate utility parameter factor to analyze the game data, determines the contradiction between the internal factors of the mine landslide risk and the utility of the external factors, and conducts the risk assessment with dynamic criteria. The experimental results show that the improved mine landslide risk assessment model is clear and reliable, and the accuracy of the assessment results is greatly improved.