time seris prediction using AR(1) model

Hi all, I want to forecast/ predict a time series based on first order Auto Regressive modeles,AR(1). The time series which called "q". For this aim I have done steps below:

- Time series standardization using mean and standard deviation.

- estimation of AR(1) parameter.

The computer programming for above operations is below:

    clc; clear; 
    close all;      

    q=[50 38 31 24 37 56 54 39  40  38  59  89  41  42  42  26  38  26  25  20  28  33  23]'; 
    mue=mean(q); 
    stdvn=std(q);
    q_standardized =(q-mue)./stdvn; 

    ar_parameter= ar(q_standardized,1)
    present(ar_parameter);

The output of the program is:

      Discrete-time IDPOLY model: A(q)y(t) = e(t(
      A(q) = 1 - 0.4559 q^-1                                      
      Loss function 0.773834 and  FPE 0.841124                     
      Sampling interval: 1                                        
      Discrete-time IDPOLY model: A(q)y(t) = e(t) 
      A(q) = 1 - 0.4559 (+-0.1924) q^-1

I need to predict 1000 numbers for t+1 time step using "q" set, which called "qt+1", and follows AR(1) models parameter. How can I do it. |Any help would be appreciated.