程序为library(grid)

library(MASS)

library(neuralnet)

library(data.table)

ydata=fread('C:/Users/iPin1995/Desktop/data.csv')

trainingdata1=as.data.frame(ydata)

colnames(trainingdata1) <-c("year","people","car","road","keyun","huoyun")

traininginput <-as.matrix(trainingdata1[1:20,2:4])

trainingoutput <- as.matrix(trainingdata1[1:20,5:6])

trainingdata <- cbind(traininginput,trainingoutput)

trainingdata<- as.data.frame(trainingdata)

net1 <-neuralnet(keyun+huoyun~people+car+road,data=trainingdata, hidden=8,threshold=0.01,stepmax = 5e+04)

data=as.data.frame(trainingdata1[1:22,2:4])

net.results <- compute(net1,data)

print(net.results$net.result)

运行结果为

          [,1]   [,2]

1  21108.75021 9401.4

2  21108.75021 9401.4

3  21108.75021 9401.4

4  21108.75021 9401.4

5  21108.75021 9401.4

6  21108.75021 9401.4

7  21108.75021 9401.4

8  21108.75021 9401.4

9  21108.75021 9401.4

10 21108.75021 9401.4

11 21108.75021 9401.4

12 21108.75021 9401.4

13 21108.75021 9401.4

14 21108.75021 9401.4

15 21108.75021 9401.4

16 21108.75021 9401.4

17 21108.75021 9401.4

18 21108.75021 9401.4

19 21108.75021 9401.4

20 21108.75021 9401.4

21 21108.75021 9401.4

22 21108.75021 9401.4