PRO ERFORMANCE ANALYSIS IME SERIE FRO REC ING There are 5 problems that you have

Question

PRO ERFORMANCE ANALYSIS IME SERIE FRO REC ING There are 5 problems that you have to solve for these projects. All the problems should be solved in one program. So, you have to create a menu system, where select 1 is for problem 1 and so on 1. 2. You should save project program name as: A100_A200_A300_project1.py (where A100,A200,A300 members id in your group.) 3. Upload project 1 to 'Assignment: project 1' in Kalam by 23/12/17 12pm File: wldata.txt Qi(t-2) 3768 3766 3764 3762 3760 3758 3756 3754 3752 3750 3744 3739 Qi(t-1) 3756 3754 3752 3750 3744 3739 3733 3727 3721 3715 3709 3705 Qi(t) 3733 3727 3721 3715 3709 3705 3704 3702 3701 3699 3698 3696 Qi 3704 3702 3701 3699 3698 3696 3695 3693 3692 3690 3688 3686 Qm 3718 3709 3701 3692 3687 3684 3687 3689 3691 3693 3696 3695 Instruction: Read file wldata.csv or wldata.txt and solved below problems. If use file wldata.csv, in your coding the split should like eachline.split(",") where in the bracket is comma string because .csv have comma in between data. ERRORI 1. AverageError= 2 marks] 2 marks] [1 marks] 2 marks)] Highest Error and line number. Percentage of error above 500. And save the data line into file error500.txt/csv Use of functions 4. 5. 2 marks] 1 marks] Where Qi is observed water level data and Qm is model output water level data Qmean is the average of Qi. N is the number of records (data). Error is Qi-Om

Explanation / Answer

Using R:

data=read.table("C:\Users\hp\Documents\widata.txt",header=TRUE)
> data
Qi.t.2. Qi.t.1. Qi.t. Qi Qm
1 3768 3756 3733 3704 3718
2 3766 3754 3727 3702 3709
3 3764 3752 3721 3701 3701
4 3762 3750 3715 3699 3692
5 3760 3744 3709 3698 3687
6 3758 3739 3705 3696 3684
7 3756 3733 3704 3695 3687
8 3754 3727 3702 3693 3689
9 3752 3721 3701 3692 3691
10 3750 3715 3699 3690 3693
11 3744 3709 3698 3688 3696
12 3739 3705 3696 3686 3695

Qi=data$Qi
> Qm=data$Qm
> ERROR=Qi-Qm

ERROR
[1] -14 -7 0 7 11 12 8 4 1 -3 -8 -9
> rmse(ERROR)
Error in rmse(ERROR) : could not find function "rmse"
> Average=sum(ERROR)/12
> Average
[1] 0.1666667
> sqerror= ERROR^2
> sqerror
[1] 196 49 0 49 121 144 64 16 1 9 64 81
> RMSE=sqrt(sum(sqerror)/12)
> RMSE
[1] 8.13429
> Qmean=sum(Qi)/12
> Qmean
[1] 3695.333
> NSC=1-sum(sqerror)/sum((Qi-Qmean)^2)
> NSC
[1] -1.213755
> highest_error=max(ERROR)
> highest_error
[1] 12

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