Fig 1.
Information level of resumes.
Fig 2.
The forward propagation and backward propagation processes in BPNN.
Table 1.
BPNN parameter setting.
Table 2.
Experimental hardware and software environment.
Fig 3.
The training process for the salary forecast model.
Fig 4.
Comparison of training results of different numbers of neurons in the hidden layer.
Fig 5.
Comparison of the convergence speed of different optimization methods.
Fig 6.
Comparison of training results of different optimization methods.
Fig 7.
Analysis of salary relevance.
Fig 8.
The relationship between dependent variables and salary.
a) Job type; b) Work experience; c) Education level.
Fig 9.
Resume information distribution.
a) Applicant department status; b) Resume information status.
Fig 10.
The fitting effect of Nadm-optimized salary forecast model.
Fig 11.
Comparison of salary forecast results of different algorithms.
Fig 12.
Comparison of salary forecast results of different NN algorithms.