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(1)

二階徵分方程式的解法及其估計

THE METHODS AND ERROR ESTlMATIONS ON THE SECOND-ORDER

DIFFERENTIAL EQUAT工ONS. w a

--hu • L SC -a v-nr bet Rs b qA n a y

工 n this paper

,

we solve the 工 nitial Value Problem (IVP)

by a Modified Predictor-Corrector method. We can prove i t

has trucncation error Q(h4 ) and i t is stable. For Boundary

Value Problems (BVP)

,

Shooting method and Finite-Difference

method are often used. We improve these methods and get some theorems and error estimations.

(2)

師大學報第卅二期

THE METHODS AND ERROk .t; ST 工 MAT 工 ONS ON THE

SECOND-ORDER D 工 FFERENTIAL EQUAT 工 ONS

REN-SHIAW YANG

DEPARTMENT OF MATHEMAT 工 CS

TAIWAN NORMAL UN 工 VERSITY

TA 工 PE 工, TA 工 WAN , R. O. C.

工 NTRODUCTION

工 n this paper

,

we will discuss two types of the second

order differential eguations of the following form:

(工 y" = f(x,y,y') , a < x < b and (P) y(a) = c y' (a) =.d _y" + f(y) =0 y (a) =c y (b) =d

,

a < x< b

On the f i r s t type 工), there' are many packages

developed such as PHASER which involves Euler's Method [7]

,

工 mproved Euler's Method [5] and Runge-Kutta Method [6]. But

for more accurate

,

we use multistep methods and then

predic-tor-corrector techniques is can also be developed. For

controlling the error

,

the main purpose is each component

must be accurate. So wedevelop a modified method (combine

Runge-Kutta Method

,

Adams~Bashforth Method [5] and

Adams-Moulton Method [5]) and take.a small number r (seè step 2 .òf

the following algorithm) to solve this system (主) •

On the second type (P)

,

Shooting Method and Difference

Method are often used. But for stability

,

we use

(3)

二階徵分方程式的解法及其估計

step 2: (Compute starting values using Runge-Kutta method.) Forward by a (very small) distance r

,

and to

calculate

Kn r

*

f(a, ya) y

a.

==y(a) ==c Yl

â.==

Ya+ ka k1d == r

*

f(a+r, Y

,

a

可 == Y

a.+

k 1a ]<;1 r

.*

f(a+ 玄,有 Y 2

&.

== Y + 2kl

kz

ð.. == r

*

f ( a + 2 r , Y 2d. ) Y2 Y

q

+ (ka+ 2kl

â.

+ 2k 1 + k2~) /6

step 3: (Adams-Bashforth three-step method for predictor and Adams-Moulton three-step method for corrector) ( s e t x = a + i h l 有Q. == Y3 + Y4 == Y3 + h {5f (x1 '叫卜 16f( 勻, Y2 )+23f (勻,Yj)}/12 h{f( 呵,可 )-5f (巧,Y2 ) + 1 9f (勻 'Y;3 ) +9f( 旬, Y咱)}/24 ) ←」 14 u s e r 、 V 』 vt e'-heL tx 一

!

←」­ ut- pu- tp- ut-ou 一 (。一

..

4. p e +」 S step 5: stop

For example

,

we will solve the followin9 initial value problem: 。 }' 「4. (-←」­ r6 )q2 X}s9 -門, LII 「3 Y{-11 f 、←」 Dιda *r*1 .lq3. PS+3 *IJ1= ﹒工可 d ﹒工 。‘一 -Dι -= E'e -一 )or 。 {e H{Eh yyyw /flstJ 、 tltk < x < 2 sqrt(2)==1.4142135...

We write a program (using above a 工 gorithm) to solve this prob18m. The program and output are listed in Appendix.

(4)

師大學報第卅二期

(1) Predictor-corrector Method for 工 nitial value problems

Suppose we will slove the initial value problem:

(工 VP)

( Y = f ( X Y Y ) y(a) = c

y' (a) =d

a < x 三 b ,

We can set upon a system equations:

( u 1 = y

,

u2 y'

u1 (a) = c

u2 (a) = d

then

,

to solve (TVP) is equivalent to solve the followihg differential equations (Q) of first order:

( u l ' = u2

,

u 1( a) =c

(Q)

l

u2" = f(x

,

u1

,

u2)

,

u2(a) = d

/ Since (Q) contains two differential equations of first order and from the predictor-corrector method techrtique for first order

,

we can develöp an algorithm as follows:

PRED 工 CTOR-CORRECTOR ALGOR 工 THM:

To approximate the solution of the initial-value problem:

f(x

,

y) a ~ x < b

,

c

Step 1:(Set initial values)

(5)

三階微分方程式的解法及其估計

We know that Adams-Bashforth Three-Step Method has

3

truncation error O(h~) and Adams-Mou 工 ton Three-Step Method

4

has truncation error O(h~) ([5]). We also know that the

predictordashcorrector method has the same order of accuracy 4

as the implicit method

,

that is O(h~) ([13]). Since the

Runge-Kutta Method of order four has local truncation error

O(h ), we conclude that this method has lo~al truncation

error O(h)

For Runge-Kutta Method

,

the local truncation error

approaches to zero as the step size approaches zerOi that

is

,

the method is convergent. Adams-Bashforth Three-Step

Method and Adams-Moulton Three-Step Method satisfy the root

condition

,

so they are also convergent. Therefore

,

the

developed method is stable.

(2) Finite Difference Method for Boundary Value problem

Consider finite difference methods for the special

class of nonlinear BVP's given by

-u" + f(u) = 0

,

0 三 x < 1 (P) u(O) = c

u( 1 ) d

Our primary concern 土 s producxing a tractable numerical

method for this problem. We shall see that

,

under fairly

mild aS5umption on f

,

that i t i5 possible to construct and

analyze for (P) which are of high accuracy. Applying the difference approximation

-u(x. -uH{XJ)2 J - 1 + 2u (x , ) - u (x. 2 h J+ 1

(6)

第卅三期 師大學報 ~ N-2

,

equations < J system of

(72-J(刊=;

2w

. -

W:'.

,

+h "f (w 布) J-1 臼 J "J+ 1 . U

.,..

J -wN- 2 + 2wN_1 + hGf(wN_1)

=

d

,

1/N is the grid spacing and Vf ~U(x~ ).

, J in matrix form as 2 0

,

-the discrete the ODE yields

(P h) to 己 ystem The 『 h 1ilhere g( 見玉, {g( 足) } j f (Wj )

,

k i s

positive gefinite

,

and 乏=(c

,

0

,....,

0

,

d ) T

The algebraic system (A) ls nonlinear

,

iteration is necessary to therf concisely written kw + h ♂-1 →RN-1 can be (Ph) (A) and kind symetric some bence g: where 。 W 戶 t approximation 。 ur produce of first decide factor multiplying g

,

to get the iteration we 。f Because step

2

, (i ) =玉- h- g(主) • convergence properties of (工 1 )

,

algebra.[2

,

at each ‘‘', 1e +h it 's-. 、 w~e bkq-V4 1-a n a k invert simply )

-T 止 { need we To nu 「4 斗 nr 們 G 4Y 戶 IY n a r o f--linear from lemma following the its A. then 11 112 T 久、 min 11 之 I~ 丘之〈JZi mx

llz||?

where "}、miniAjiλmax for a11 eig~nvalues令。 f

is symmetric and postive defnite

,

then

又 j n*n matrix

,

symmetric a 1. S A A proof: eigenvalues 工 f 工 f Lemma. its and Thus e v

--• L -L-sn 。 R p n a Dι s and real and are orthonrmal are V

恥『吋

}C.3 啊,「 d f'1-L~' 、=

-nz-3

s--aF r

YN c e v n e qd .工 e

'

、正呵, ι Y cl.

J

max

n

λ. <入 max 主 3 一

=♂ d

j =1 J yTl\.y that s 。 j =1 of convergence the lower bound. e p1J 14 司, •• a6 n3 a4

.

op ιL­ 『I qL 4. Dι the n o

--令」 -l s' 。 3 P1 [ aflk

-nh' -1

,

E T4 wt 、 。 n forλand 佇11n similarly iteration are We and the

(7)

二階微分方程式的解法及其估計

then determined by (1

1)

,

戶 (i)=1: 目 2{i) , HillIE{i}

卅一 r

,,-"'(

0)" '

f (5) 1 11 e.' v '1 m11l

11ε(1)

112

H '~hcorem : (2 ) < 、

15 the sm<llle5t cigenvalue of k.

。 l > mll1 where ) ,4 γaa { and (11.) from have-

,

We Proof: (i) g(之)) • =-112(9{2) ke (1+1)

..

』 -h I

e

-。 D ‘ m 。 c 、 J } hi ι .. 』, 1. 、 J -3w eF-A LH ←』 c0l1s1der •• EJ '} LL 、', -n1

,

qd-i .,也, E ‘ rw 呵 { eqJ I i 恥、 lerm on t:lle '1'0 ana1yze } ﹒旬, d w {-EL

=

'

} .、品 , E 、.、', e .、 J S { FA (g(~) 、

-lhus 2_ (i) = -h~De '、圖, } 可 -A + -l14 r 、 a e~n ko qd a ., .• • G Thus

.

) .、 J qH (

-SL 2 , ~(i+l) , T~_(i) -h~(e ,---, )ADe

-一 D. . JJ mat:rix with.element:s a lS where 0

=

(i+1)1'. (i+l) (e' - --, ) ke ( 3 ) right: } -l f ‘.、 J e ) ,且也 + .、品 { .可 J e } ﹒『 J RM {

,

SL 唔,晶,主 白,“= N-3 白 白 t:he (i+1),T ~_(i)

I

(皂 }DB term on the at look ^gain

,

是 maffh)||lji叫11

2

!I

!t( i

)16

we get fllhz d 到 『4

,

..

A 斗, .可 A e~ EH FA ( 3)

,

side of left: 可4 1 1 〈、 t:he

Ib(i叫I ~

。 n l using Lemma IJence, mé\x A m11l (2) . t:o immediat:ely leads which l < i f converges Ami I1 müx

I

f I (s)

I

i t:erat:ion '、 h"" = the U t:hen

,

Clearly

,

(8)

師大學報第卅二期

g:

The eigenva1ues of k do depend on N

=

1/h

,

and in fact it Cëln be 2

shoWI1 tha t.入:~ = O(h'). 'fhus u = 0(1) and so conVergenCe is.itot SQ

m~n

Dutomatic as it seems. We nced to modify (1

1) to improve matters. To improve (1

1) we 100k at thc definition of u

.

We add a COl\

st-i1llt to the diago/la1 of a matrix shifts the eigellva1ues: if

A t.

=

"'1.

I

• ,-J ,..,..,'

l.I

ic

lI

(A + vl)z = ( ,,+ y)z.

'.Iot!vated by this we add:!: v.'己 i l1 to (A) to get

(A ' ) (k+VI )if+(h29{3) - v~)

=

.、,r

,

which leads to the i l:eration

E

Ta-{ ( i+ 1) _._ I L 2 _ I • • ( i ) \ .... ( i )

(k + vI) 之=! - (h~g( X!\-')

^"

ana1ysis simi1ar 1:0 thal: used in Theorem 1 shows that

,

for

_ (i) ;::J ( i )

=

w - w'-' . we nave 9桐、"

11 兒(

i ) 11 2 <

(u

(v)

1

i 11

~(

0 ) 112 where u(v)

=

) s { ZL 『4 l v xR nuιLW ms v

+"

nun

obvious1y we want to choose v 50 that u(v) < 1

,

andu(v) is as small

i1S possib1e.

Theorem 2: I f f '(s }iEOfor al l.s , and vZhzmax f '(s ),

v - h2 min f'(s)

then

u (v)

=

<1

v ... " m~n för a11 h.

(9)

二階微分-方程式的解法及其估計 1、 roof: UIlJcr lhe hypolhcsns of f nnd v

,

max

I

v - .h 2 f ' (口 )|=max(v-i12f'{s)),

=

v 呵 h

2

min

f'(5)

,

which i5 strictly le55 than v

.

lJut v +λ>v , hence the rati 。

m~n

u(v)< .1.

Since u(v) is a non-decreasillg function for v 主 0 , we wish t 。

take v a5 small as possible to a~lieve minimum convergence factor

u(v). Theorem 2 appears to give. condltions for finding the optimal

v

,

but in fact dοes not. Because Theorem 2 gives only sufficient conditions for u(v) <1

,

not neces.ary ones; u(v) <1 is p 。正sible even when the hypotheses of Theoem 2 do' not hold. Generally

,

(I

r )wil1

converge so lol\g as f' (s) ~ 0 on a larg.e enough interval containil\g

會 he boundary values.

We are now toexamine theerror in approximating solutions

to (P) using our nonlinear algorithm. The analysis foilows mucll

lhe same lines as the linear casc. If the vector 均=

f

u,( X j)I i s the vector of the exact solution evaluated at x.;' l~ j 乏 N-l , then

3

(4 ) KEa

+1129( 山}=r+112z ,

可?戶﹒

<:h2

,

where C d

r.

pcnds ollly on the c;ierü;atives of u

,.

叫 th 11 7. 11正

Subtracting $4) and (A) we get

k(足, -23)+h2{9{E,}-9{1))=

2z~ 2z~ -n

--YN D 司正 ku

'

+ WM 「 k u~r 、 = Y

r 。 SL O S

where D is a diagonal matrix with entries Dj = i4xj)and wyThus

(10)

闕 ,甜甜

"

可 -a D 弓,必 』 H + 'bhi 呵, h

iE

ZEh--C

=〈\昌 ﹒『 .J W ﹒『 Ed x "可 M 間 ,、、 期似 .o •

-mo

卅 第 報。 學 大 師

based on the f0110wing 1emma.

Lemma z zf Dj=f'{sj}and E '{s }事。~"> 0

,

for a11 5

,

then

II(

I(

k + h k

+

h 20 ) -2 0 ) -

111,國<

J 1/(h20").

Proof: k+ h20 = Q(1 -C)

,

where Q i5 diagonal

,

Qj = 2 + h20j

,

and each row of C has at most two non-zero entries

,

viz.

,

=-l/{2+112D. } , C =-l/(2+lE2D ).

j-l -

-..., \'

,- JI Uj_l" "j+1 -

...,

\~

..

....j+1

月l'hus

~cll...

<2/(2 +

h

2

,σ)

< 1 .and s 。

II(k

+ h20)-l

.11..

~

IIQ-

1

IL [

1 _

~clI...

J

l

r

1 < 、 2 + h-a- I 1- --~-2 + h-(7" l

-2 +

h

2

,σ-

2 自

=1/(11;σ}

We have thus estab1ished

,

under the condition f'(s)3 (7" >0

,

that

-1.2 !u

,

(x..:) - W.!! .5 C

,IT'

-"'h

O~ j這 N'

-,'

"j , .. j 、 l

where C

1 depends onbounds for the third and fourth derivatives of u

.

(i)

since we a1most a1ways are working w1th ~\~I instead of ~

,

we 11.. ..(1)/1

have the addi tiona1 error term ,. 11 w - W

\...,

11

(11)

二階微分方程式的解法及其估計 ( i) I lu(x.!) -w~"'/1 O 吉 j 空 N J J 、

11 旦- ~II...

+

1

~ -兌付) 11 阿

< < 、 cf-lt12+!ls-di}lL

,

C

1

~1h2

+

(u(V))ill~112

' ( 0)

assurnir193zo . w e thus are interested in taki 呵 i 1ar.ge enough

so that

i ".. 2

(u(v)}.I.

=

Q(h"'")

,

in order to preserve accuracy.

REFERENCES

[1) A1exander

,

R.

,

Diagona11y implicit Runge-Kutta method~ f。早

stiff O.D.E.'s

,

SIAM J.Numer. Anal.

,

14

,

1977

[2) Atkinson

,

k.

,

An Introduction to Numerical Analysis. John Wiley, New York ,工 978

[)) Boyce

,

W.and R.Diprima

,

Elementary Differential Equations

,

3rd.

,

John.Wi1ey

,

New York

,

1977.

[4) Bulirsch

,

R. and J.Stoer

,

Numcrical treatment of ordinary

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,

Numer.Math.

,

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,

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,

J. and Reyno1ds

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A.

,

Numerica1 Analysis

,

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,

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,

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[6) Butcher

,

J.

,

On the attainable order of Runge-Kutta methods

,

Math.Comp.

,

1'

,

1965

,

pp. 408-417.

[7) Ceschino

,

F. and J. Kuntzmann

,

Numerica1 So1ution of 工 nitial

Va1ue Prob1ems

,

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,

Englewood Cliffs

,

N.J.

,

1966.

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,

L.

,

and N. Levinson

,

Theory.of Ordinary Different-ial Equations

,

McGraw;-lIi l l

,

New York

,

1966.

(12)

different-師大學報第卅二期

ial equations

,

in Mathematical Software

,

J. Rice

,

ed.

,

Academic Press

,

New York

,

1971

,

pp.477-507

[10JGear

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C.W.

,

Numerical Initial Value Problems in Ordinary Diff-erentìal Equat!ons

,

Prentice-IJall

,

Englewood Cliffs

,

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,

1971. [IIJGragg

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W.

,

On extrapolatlon algorithms for ordinary initial

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,

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2

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,

pp.384-403..

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R.

,

Numerical Methods

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Englewood Cliffs

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,

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[13J Issacon

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E.

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and II.Keller

,

Analysis of Numerical Methods

,

John Wiley

,

New York

,

1966.

[14J Keller

,

II.

,

Numerical Methods for Two~Point 80undary Value Problems

,

Ginn-81aisdell

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Will tham.

,

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[15J Keller

,

II.

,

Numerical Solution of Two-point 80uridary Value Problems

,

Regional Conf. Series 1n Appl.Math~12~ , SIAM , Phil-adelphia,1976.

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,

Numerical Solution of Ordinary Differential Equations

,

John Wiley

,

New YorJ屯, 1965.

[17] Shal1)lPine;L. and M.Gordon

,

Computer Solution of Differential

(13)

二階傲分方程式的解法及其估計

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(14)

師大學報第-JIt二期 LIHE I O/HEST LVL '。 7." 。 "Enu ﹒'、 4.2.qq' ,包,'"。 "Emu-' ,'‘‘ 3. 旬,言,。 7."un3 《 u. ,筍,‘, 3'" ,、', b' ,俏。 "3 向 u. , -4 , 2." ,、',旬,''"。 "Emu-' 旬,., 3." , 2 , b 可 '"En3O EdRdFDR' , b'" ,。'。, b'b' 。, b' 。'。可',',旬,',、',、',,旬,呵,旬, '"nnE 胸口 monomonoaonunon3"3qdn3n3"3n3nERER3nMOOnunununνnununuI 11111111111 }}}}}}}}}}1}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}}} ‘'‘.'‘‘'‘司,‘呵,‘‘'‘‘'‘角,‘‘',‘‘',‘司,‘‘'‘呵,‘司,‘‘, •• ,.唔,且,‘' •• ,.司, •• '‘喝,‘.'‘司, •• ' •• '‘‘'‘‘'‘",‘角,‘‘',.呵,.司, a •• , z •• ', •• sa--' ,.旬,‘嚕,‘‘'‘‘,‘旬,,.呵,‘.'‘‘,“ -dy MHHHHHHHHHHHHHHHHHHHHHHHHHHHMHMHMHHHHHM 肉""“阿 HHU 間 HHHHHHH"HHMHHNAU 阿 HHHHHNHNHNHNM 伺 unnunu"UMHHN -e ﹒',‘有 4 、 4 , -zdZJZJZJZdzdtd 司 d 『 d ﹒句.“﹒旬,‘ dzd 司 dL 可."﹒句有 d 且, 2."-h 『﹒ ι 甸甸‘ J2J 電 d-h 『﹒旬, h『 L 呵,‘ d1d ‘ 4 •••• "、‘ 4 , hu--' ,‘ nu'' ,且 ,‘',‘ d' ‘ d

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(15)

二階徵分方程式的解法及其估計

llNE I O/"EST lVL < STAIIFORO PASCAl

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(16)

師大學報第卅二期

lINE' D/NEST lVl < ST^NFORD P^SCAl, MCGlll VERSION OF M^Y -B~ > 10:22:15 05

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(17)

二階徵分方程式的解法及其估計 x- 0.0000 Y ﹒ 2.1213203~ 7.&&~32~~0 c- 7.6 的 32 仙。 -20.93659259 x- 0.0010 Y- 2.12897~18 7.&~335496 c- 1.643]5496 -21.002263~1 x- 0.0020 Y- 2.13660703 7.6223199~ ç- 7.62231994 -21.06712695 x- 0.00]0 y. 2.1"21880 1.60121957 c- 1.60121951 -21.13298255 x- 0.00'0 Y- 2.151809'~ 1.58005~05 ç- 1.58005405 -21.19802959 x- 0.0050 Yω2.'5937889 7.55882358 0-. 1.55882358 -21.26286140 X- 0.0060 Y- 2.16692707 7.53752838 c- 1.53752838 -21.32749536 Xa 0.0070 Y- 2.114'5392 1;51616866 c- 1.51&16866 -21.]9191283 Xa 0.0080 y. 2.18195939 7.4947'46] 0- 7..947.'63 -21.'5611916 X- 0.0090 Y- 2.189.4339 7.473256'9 c- 1..73256'9 -21.5201137' x- 0.0100 y. 2.1969058 日 1.'5170'41 c- 1..5170447 -21.58]89592 AT X • 0.00000 Y AHO O.AnE 2.121]20]4 1.66432"0 1.664]2 仙。 -20.93659259 AT X • 0.00500 Y ^HO G AnE 2.15937889 7.55882358 1.55882]58-21.26286740 nuFEmu-旬,',‘'"草,旬,眉,‘ dnu ﹒句俏旦司,‘, bnu 司 4nunv'b 唔,',、 d'huanuamw 司 4 嚕,‘司 d ‘ 3.B.M •• ", hv-z 司 dRHwqd7'" 。, b r2qdnpRd 『'‘ onE"ERE 唔, appq4nE' •• Jnum 耳, '"o.s -h 『唔,,苟,',“ •. nwd 筍,‘‘‘ J' ‘ d ﹒ '"wdtb 司,',可', -u 可 mwd 峙,‘'‘'‘‘ J ﹒壘, Rwd 'h •• 4-4 ,huEd--RURu--FhJ'hw 旬,‘‘ 4 ,hvRd--nunnv-BP 呵, -ELM-L-y ﹒ 1 , hu--, s.g.-‘ 4 , b ﹒', b 『 L 可 -4 , hu-3.1 •• ', .'hu RHU-h 『 -huτ" “",‘ J. “可,‘且,‘‘ d-h 可‘‘ JnNHWEU 旬,包, -aMU' ‘ J-b 呵,‘ J ‘‘', -u 『'‘ J ZJ 句,‘司 41dqdL 呵, h" , bL 可 qdzd-4 『 dtdq' ,.“旬, hv'bsb 『 qd

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(18)

二階徵分方程式的解法及其估計

二階微分方程式的解法及其估計

摘要 數學系﹒楊岳孝 本丈中,我們將研究下列二種類別的二階微分方程式之修飾解法: ( 1)

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+f(y)=O

,

a 至 x 三三 b -{ y(a)=c \. y (b)=d 對於第一類型( 1 )的解法,目前有套裝軟體發展,如 P~SER ,其中使用的

方法有 Euler's Method , Improved Eùler's Method 及 Runge-Kutta Met-hod 。但為使解更精確,我們探用 Multistep rnethod 旦使用 predictor-

corr-ector 的技巧,通常,我們為了控制錯誤至最小,最主要是要使每一部分的答案

均應準確。因此,我們發展一修飾的解法(融合 Runge-kutta Method, Adams

";" Bashforth Method

,

Adams -Moulton Method )並適當選取一小數 r (見第 一部分文中演算法之步驟 2 )來解此問題。

對於第二類型 (P) 的解法通常使用打靶法及有限差分法,但為顧及穩定性, 我們探用有限差分法後再加以改進。然後,我們再討論此解法具較高的精確度。

參考文獻

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