install.packages("xlsx")
install.packages("nnet")
library(xlsx)
library(nnet)

data<-read.xlsx2(file.choose(),1)
data
plot(df$ÀÏÀÚ,df$ÇöÀçÁö¼ö)
grid()


data$ÇöÀçÁö¼ö<-gsub(",","",data$ÇöÀçÁö¼ö)
data$ÇöÀçÁö¼ö<-as.numeric(data$ÇöÀçÁö¼ö)
df<-data.frame(ÀÏÀÚ=data$³â.¿ù.ÀÏ,ÇöÀçÁö¼ö=data$ÇöÀçÁö¼ö)
df
plot(df$ÀÏÀÚ,df$ÇöÀçÁö¼ö,xlab="ÀÏÀÚ",ylab="Á¾°¡",type="o")

getDataSet<-function(item,from,to,size){
  dataframe<-NULL
  to<-to-size+1
  for(i in from:to) {
    start<-i
    end<-start+size-1
    temp<-item[c(start:end)]
    dataframe<-rbind(dataframe,t(temp))
  }
  return(dataframe)
}

INPUT_NODES<-10
HIDDEN_NODES<-INPUT_NODES*2
OUTPUT_NODES<-5
ITERATION<-500

in_learning<-getDataSet(df$ÇöÀçÁö¼ö,1,102,INPUT_NODES)
in_learning

out_learning<-getDataSet(df$ÇöÀçÁö¼ö,11,107,OUTPUT_NODES)
out_learning

model<-nnet(in_learning,out_learning,size=HIDDEN_NODES,linout = TRUE,rang = 0.1,skip=TRUE,maxit = ITERATION)

in_forecasting<-getDataSet(df$ÇöÀçÁö¼ö,98,107,INPUT_NODES)
in_forecasting

predicted_values<-predict(model,in_forecasting,type="raw")
predicted_values

real<-getDataSet(df$ÇöÀçÁö¼ö,108,112,OUTPUT_NODES)
real

ERR<-abs(real-predicted_values)
MAPE<-mean(ERR/real)*100
MAPE

plot(c(1:5),real, type="o", col="blue")
lines(c(1:5),predicted_values, type="o", col="red")

## ¿¹ÃøÇϱâ

in_learning<-getDataSet(df$ÇöÀçÁö¼ö,1,107,INPUT_NODES)
in_learning

out_learning<-getDataSet(df$ÇöÀçÁö¼ö,11,112,OUTPUT_NODES)
out_learning

model<-nnet(in_learning,out_learning,size=HIDDEN_NODES,linout = TRUE,rang = 0.1,skip=TRUE,maxit = ITERATION)

in_forecasting<-getDataSet(df$ÇöÀçÁö¼ö,103,112,INPUT_NODES)
in_forecasting

predicted_values<-predict(model,in_forecasting,type="raw")
predicted_values

real<-df$ÇöÀçÁö¼ö[103:112]
real

plot(1:10,real,xlab="±â°£",ylab="Á¾°¡",xlim=c(0,15),ylim=c(2300,2400),type="o")
lines(11:15,predicted_values,type="o",col="red")
grid()
plot(df$ÀÏÀÚ,df$ÇöÀçÁö¼ö)
lines(df$ÀÏÀÚ[113:117],predicted_values,type="o",col="red")