Prediksi Banjir DKI (Jakarta) dengan Anfis

1. Prediksi Iklim dan Banjir
DKI dengan Anfis
The Houw Liong
P.M.Siregar
R.Gernowo
H.Widodo
S. Nuryanto

2. Garis Besar
•
•
•
•
•
•
•
Model Iklim dan Cuaca
Hard Computing & Soft Computing
Prediktibilitas , Chaos/Weak Causality
Kaidah Fuzzy & ANFIS
Fuzzy Clustering
Deret Waktu Bilangan Bintik Matahari, Curah
Hujan & Tinggi Muka Air
Kesimpulan

3. Model Atmosfer

4. Model Atmosfer

5. Physical Model
• Cloud Formation : Arakawa , Kuo
• Interactions : lands, oceans, cryosphere,
•
biosphere
Forcing : Solar activity, volcanic eruptions,
cosmic rays
• Predictability
• Chaos, Attractor, weak causality

6. Predictability of a Climate Model

8. Forecasting Based on Soft
Computing & Solar cycle
• Quasi periodic solar cycle
• Sunspot , flare , cme, galactic cosmic
rays, interplanetary magnetic field and
weather
• ENSO & IOD
• MJO

9. Sunspot & cosmic ray

10. Galactic Cosmic Rays

11. Cosmic Rays

12. Kaidah Samar Sugeno
(Sugeno Fuzzy Rules)
• Untuk x adalah Ai dan y adalah Bj maka z
adalah pix + qjy + rij
• Kaidah Belajar /Learning Rules :
• δv_k = - η∂e_tot/∂v_k

13. Adaptive Neuro Fuzzy Inference
System
layer 1
layer 2
layer 4
A1
∏
w1
A2
N
B1
N
∏
B2
x y
layer 3
layer 5
w1
w2
w2
x y

14. ANFIS
•
Layer 1 :
•
•
•
•
•
•
O1,i = µAi ( x),
for
i =1, 2, or
O1,i = µBi−2 ( y ),
•
for
i = 3, 4,
x and y are input of ode -i and O1,i is
membership function of fuzzy set A=(A1,A2)
and B=(B1 ,B2 ) with membership function
A is :
1
µ (x) =
A
x− i
c
1+
ai
2b
O 2,i = w 1 = µ Ai (x) µ Bi ( y) i = 1,2
ai,bi, and ci are parameters
Layer 2 : output as the product of input
membership functions :

15. • Layer 3 in node -i :
•
wi
O 3,i = w i =
w1 + w 2
, i = 1,2
• Layer 4 : Node -i is
adaptive node with function
node :
O 4,i = w i f i = w i (p i x + q i y + ri )

16. ANFIS
• Layer 5 : final output :
•
O5 =
∑ wi f i =
i
∑w f
∑w
i i
i
i
i

17. sspot
200
150
100
50
0
2012
2008
2004
2000
1996
1992
1988
1984
1980
1976
1972
1968
1964
1960
1956
1952
1948
sspot

18. NASA : Prediction of Solar Cycle
24

19. Pontianak Region
Correlation Sunspot vs Precip =0.88
Sunspot/Precip
200.00
200.00
150.00
100.00
50.00
0.00
-50.00
150.00
100.00
50.00
0.00
2002
1999
ave-precip
1996
ave-sunspot
1993
1990
1987
1984
1981
1978
1975
1972
1969
1966
1963
1960
1957
1954
1951
1948
Years

20. mm/month
Jaya Pura
350.00
300.00
250.00
200.00
150.00
100.00
50.00
0.00
200.00
150.00
100.00
50.00
0.00
2002
1999
1996
1993
1990
1987
1984
1981
1978
1975
1972
1969
1966
1963
1960
1957
1954
1951
1948
Years
Avg precip
sspot

21. Jakarta
200.00
200.00
150.00
150.00
100.00
100.00
50.00
50.00
0.00
0.00
1948
1951
1954
1957
1960
1963
1966
1969
1972
1975
1978
1981
1984
1987
1990
1993
1996
1999
2002
mm/month
250.00
Years
Avg Precip
Avg-sspot

22. Fuzzy Clustering
• Fuzzy c-means Algorithm
• Fix c (2≤c≤ n) and select a value for parameter m’,
initialize the partition matrix U(0), membership
functions and the centers . Each step in this
algorithm will labeled r, where r=0,1,2,..
• Repeat updating the partition matrix for rth step,U (r)
•
until
U
( r +1)
−U
(r )
≤ε

23. Fuzzy Clustering
• set r=r+1
• Calculate the new c centers :
n
m'.x
∑µ
ik kj
k=
1
vij =
n
m'
∑µ
ik
k=
1

24. • Calculate the new membership functions
−1

(r +1) =
µ
ik

2/(m'− 1)
 (r ) 




 c d 

 ∑  ik 

 j =1 (r ) 

 d jk 









25. • set r=r+1
• Calculate the new c centers :
n
m'.x
∑µ
ik kj
k=
1
vij =
n
m'
∑µ
ik
k=
1

26. Pengelompokan Samar (Fuzzy
Clustering)

27. IOD from PAOMA Forecasts

28. Multivariate Enso Index

29. Prediksi Curah Hujan Ciliwung Hilir
(DKI Jakarta)
Ciliw ung Hilir Prediksi September 2009 - Maret 2010
Cur Hujan (x100 mm)
8
Data
Prediksi ANFIS
Oct-04
Jul-05
6
4
2
0
Jan-04
Apr-06
Jan-07
Oct-07
Jumlah Bulanan Rata-Rata
Jul-08
Apr-09
Jan-10

30. Prediksi Pentad Ciliwung Hilir
2.5
Ciliw ung Hilir Prediksi Oktober 2009-November 2009
Cur Huj (x100mm)
Data
Prediksi ANFIS
3-Jun-09
3-Oct-09
2
1.5
1
0.5
0
3-Jun-08
3-Oct-08
3-Feb-09
PENTAD

31. Prediksi Curah Hujan Ciliwung Hulu
Ciliw ung Hulu Prediksi September 2009 - Maret 2010
8
Cur Hujan (x100 mm)
Data
Prediksi ANFIS
6
4
2
0
Jan-04
Sep-04
May-05
Jan-06
Sep-06 May-07 Jan-08
Jumlah Bulanan Rata-Rata
Sep-08
May-09
Jan-10

32. Cur Huj (x100mm).
Curah Hujan Pentad Ciliwung Hulu
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
3-Jun-08
Ciliw ung Hulu Prediksi Oktober 2009 - November 2009
Data
Prediksii ANFIS
1-Oct-08
29-Jan-09
PENTAD
29-May-09
26-Sep-09

33. Analisis Hujan Ekstrim DKI dengan
WRF

34. Data Curah Hujan 2007 BMKG serupa
dengan Hasil WRF

35. Kesimpulan
• ANFIS & Pengelompokan Samar dapat
digabungkan untuk prediksi/ prakiraan
Iklim jangka panjang dan menegah.
• Prediksi cuaca jangka pendek yang akurat
memerlukan model atmosfer dan data
radar & satellit cuaca.

37. Banjir 2002

38. Ciliw ung Hilir Prediksi Agustus 2008 - April 2009
Cur Hujan (x100 mm)
8
Data
Prediksi ANFIS
6
4
2
0
Jan-04
3
Jul-04
Jan-05
Jul-05
Jan-06 Jul-06 Jan-07 Jul-07
Jumlah Bulanan Rata-Rata
Jul-08
Jan-09
Ciliw ung Hilir Prediksi September 2008-December 2008
Data
2.5
Cur Huj (x100mm)
Jan-08
Prediksi ANFIS
3-Aug-08
3-Nov-08
2
1.5
1
0.5
0
3-Aug-07
3-Nov-07
3-Feb-08
3-May-08
PENTAD

39. Ciliw ung Hulu Prediksi May 2008 - April 2009
8
Cur Hujan (x100 mm)
Data
Prediksi ANFIS
6
4
2
0
Jan-04
Jul-04
Jan-05
Jul-05
Jan-08
Jul-08
Jan-09
Ciliw ung Hulu Prediksi May 2008 - Desember 2008
2.5
Data
Cur Huj (x100mm)
Jan-06 Jul-06 Jan-07 Jul-07
Jumlah Bulanan Rata-Rata
Prediksii ANFIS
2
1.5
1
0.5
0
2-Sep-07
1-Dec-07
29-Feb-08
29-May-08
PENTAD
27-Aug-08
25-Nov-08

40. Banjir 2005

41. 0
KELAS
>55
>50-<=55
>45-<=50
>40-<=45
>35-<=40
>30-<=35
>25-<=30
>20-<=25
>15-<=20
>10-<=15
>5-<=10
0-<=5
PROB (%)
>55
>50-<=55
>45-<=50
>40-<=45
>35-<=40
>30-<=35
>25-<=30
>20-<=25
>15-<=20
>10-<=15
>5-<=10
0-<=5
PROB (%)
PROBABILITAS
INTENSITAS Curah Hujan
INTENSITAS C.H. ( 1957 - 1988 ) JAKARTA (745 )
60
50
40
30
20
10
0
KELAS
INTENSITAS C.H. ( 1985 - 2003 ) BOGOR
60
50
40
30
20
10

42. 0.00
-0.20
2017
2014
2011
2008
2005
2002
1999
1996
1993
1990
1987
1984
1981
1978
1975
1972
1969
1966
1963
1960
1957
1954
1951
1948
IOD
IOD
IOD
0.60
0.40
0.20
-0.40
-0.60
Years

43. Solar activities & Climate

44. Negative
Positive
Years
sspot
1998
2000
2002
2000
2002
1988
1986
1984
1982
1980
1978
1976
1974
1972
1970
1968
1966
1964
1962
1960
1958
1956
1954
1952
1950
1998
0,00
1996
50,00
1996
100,00
1994
150,00
1994
200,00
1992
Positive-Negative of Indian Dipole Mode Years
1992
sspot
1990
Years
1990
1988
1986
1984
1982
1980
1978
Elnino
1976
1974
1972
1970
1968
1966
Lanina
1964
1962
1960
1958
1956
1954
1952
1950
1948
0,00
1948
Sunspot Number
Sunspot Number
Elnino-Lanina Years
200,00
150,00
100,00
50,00