基于MFO优化BP神经网络的高校校园安全评价

Evaluation of Campus Safety in Colleges and Universities Based on BP Neural Network Improved By MFO

为提高高校校园安全评价的精度,提出一种基于MFO-BP的高校校园安全评价方法。首先运用层次分析法构建高校校园安全评价指标体系,其中一级指标4个、二级指标21个。之后,将影响高校校园安全的21个二级评价指标得分作为MFO-BP的输入,高校校园安全综合得分作为MFO-BP的输出。研究结果表明,与GA-BP、PSO-BP和BP相比,MFO-BP可以有效提高高校校园安全评价精度,为高校校园安全评价提供了新的方法。

In order to improve the accuracy of campus safety evaluation,a new method of campus safety evaluation based on MFO-BP is proposed.Firstly,the system of university campus safety evaluation index is constructed by the analytic hierarchy process,including 4 primary indicators and 21 secondary indicators.Afterwards,the score of 21 secondary evaluation indicators that affect the safety of university campuses was used as the input of MFO-BP,and the comprehensive score of university campus safety was used as the output of MFO-BP.The results show that compared with GA-BP,PSO-BP and BP,MFO-BP can effectively improve the accuracy of campus safety evaluation and provide a new method for campus safety evaluation.