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715211229

ľ³æ (ÕýʽдÊÖ)

[ÇóÖú] matlabÄâºÏ¹«Ê½ÖÐδ֪ϵÊý

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5¡¢¸ßËÙ͹ÂÖ½øÆøÃÅÉÏÉý¶Î
f(x) = a6*(x^24)+a5*(x^22)+a4*(x^16)+a3*(x^12)+a2*(x^6)+a1*(x^2)+a0

       a0 =       5.675  (5.669, 5.68)
       a1 =      -9.946  (-9.978, -9.915)
       a2 =        6.59  (6.513, 6.667)
       a3 =       -3.32  (-3.421, -3.219)
       a4 =        1.42  (1.357, 1.482)
       a5 =     -0.2558  (-0.272, -0.2396)
       a6 =     0.08181  (0.07615, 0.08747)

6¡¢¸ßËÙ͹ÂÖ½øÆøÃÅϽµ¶Î  £¨Ð§¹û²»ºÃ£©

       f(x) = a6*(x^26)+a5*(x^22)+a4*(x^20)+a3*(x^18)+a2*(x^5)+a1*(x^2)+a0

       a0 =       5.674  (5.625, 5.723)
       a1 =      -16.34  (-16.67, -16.01)
       a2 =       15.89  (15.25, 16.52)
       a3 =      -66.16  (-73.4, -58.92)
       a4 =         110  (97.04, 123)
       a5 =      -52.58  (-59.2, -45.96)
       a6 =       3.717  (3.193, 4.24)


[ Last edited by 715211229 on 2011-12-23 at 12:13 ]
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  • ¸½¼þ 1 : Êý¾Ý.rar
  • 2011-12-23 12:12:11, 4.31 K

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» ±¾Ö÷ÌâÏà¹Ø¼ÛÖµÌùÍÆ¼ö£¬¶ÔÄúͬÑùÓаïÖú:

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ÒÑÔÄ   »Ø¸´´ËÂ¥   ¹Ø×¢TA ¸øTA·¢ÏûÏ¢ ËÍTAºì»¨ TAµÄ»ØÌû

dbb627

ÈÙÓþ°æÖ÷ (ÖøÃûдÊÖ)

Ò»¶¨ÒªÑ¡ÄãµÄ¹«Ê½Âð
Linear model Poly9:
     f(x) = p1*x^9 + p2*x^8 + p3*x^7 + p4*x^6 +
                    p5*x^5 + p6*x^4 + p7*x^3 + p8*x^2 + p9*x + p10
Coefficients (with 95% confidence bounds):
       p1 =       2.661  (-3.745, 9.066)
       p2 =      -40.35  (-80.31, -0.3958)
       p3 =       196.5  (91.87, 301.1)
       p4 =        -447  (-596.2, -297.8)
       p5 =         526  (400.1, 652)
       p6 =      -319.1  (-383, -255.1)
       p7 =       99.43  (80.45, 118.4)
       p8 =      -24.38  (-27.42, -21.34)
       p9 =      0.7499  (0.5288, 0.971)
       p10 =       5.671  (5.666, 5.677)

Goodness of fit:
  SSE: 0.003105
  R-square: 1
  Adjusted R-square: 1
  RMSE: 0.00413

Linear model Poly9:
     f(x) = p1*x^9 + p2*x^8 + p3*x^7 + p4*x^6 +
                    p5*x^5 + p6*x^4 + p7*x^3 + p8*x^2 + p9*x + p10
Coefficients (with 95% confidence bounds):
       p1 =       396.8  (308.6, 485)
       p2 =       -2180  (-2675, -1684)
       p3 =        4874  (3706, 6042)
       p4 =       -5600  (-7100, -4100)
       p5 =        3365  (2225, 4506)
       p6 =      -888.2  (-1410, -366.8)
       p7 =        18.5  (-120.8, 157.8)
       p8 =       9.332  (-10.71, 29.38)
       p9 =      -2.033  (-3.344, -0.721)
       p10 =       5.711  (5.683, 5.739)

Goodness of fit:
  SSE: 0.07685
  R-square: 0.9999
  Adjusted R-square: 0.9999
  RMSE: 0.02139


The more you learn, the more you know, the more you know, and the more you forget. The more you forget, the less you know. So why bother to learn.
2Â¥2011-12-23 15:09:47
ÒÑÔÄ   »Ø¸´´ËÂ¥   ¹Ø×¢TA ¸øTA·¢ÏûÏ¢ ËÍTAºì»¨ TAµÄ»ØÌû

dingd

Ìú¸Ëľ³æ (Ö°Òµ×÷¼Ò)

¡¾´ð°¸¡¿Ó¦Öú»ØÌû

¸Ðл²ÎÓ룬ӦÖúÖ¸Êý +1
715211229(½ð±Ò+1): ¡ïÓаïÖú àÅ£¬Êǵģ¬ÓöàÏîʽÄâºÏ¿ÉÒÔÄâºÏµÄºÜºÃ£¬Ö»ÊÇÕâ¸öÎÊÌâ¸ø¶¨ÁË·½³Ì£¬ËùÒÔÓеã±ðŤ 2011-12-23 20:05:44
¾ÍÔ­Êý¾ÝºÍÄ£Ð͹«Ê½¶øÑÔ£¬³ý·Ç¸Ä±ä¹«Ê½£¬Ò»Â¥µÄ½á¹ûÓ¦¸Ã¾ÍÊÇ×îºÃµÄÁË¡£
3Â¥2011-12-23 16:05:27
ÒÑÔÄ   »Ø¸´´ËÂ¥   ¹Ø×¢TA ¸øTA·¢ÏûÏ¢ ËÍTAºì»¨ TAµÄ»ØÌû

715211229

ľ³æ (ÕýʽдÊÖ)

ÒýÓûØÌû:
2Â¥: Originally posted by dbb627 at 2011-12-23 15:09:47:
Ò»¶¨ÒªÑ¡ÄãµÄ¹«Ê½Âð
Linear model Poly9:
     f(x) = p1*x^9 + p2*x^8 + p3*x^7 + p4*x^6 +
                    p5*x^5 + p6*x^4 + p7*x^3 + p8*x^2 + p9*x + p10
Coefficients (with 95% confidence boun ...

Êǵģ¬Çó¸ø¶¨¹«Ê½µÄϵÊý
ÎÒÊÇÎÏÅ£
4Â¥2011-12-23 20:03:48
ÒÑÔÄ   »Ø¸´´ËÂ¥   ¹Ø×¢TA ¸øTA·¢ÏûÏ¢ ËÍTAºì»¨ TAµÄ»ØÌû

dbb627

ÈÙÓþ°æÖ÷ (ÖøÃûдÊÖ)

ÒýÓûØÌû:
4Â¥: Originally posted by 715211229 at 2011-12-23 20:03:48:
Êǵģ¬Çó¸ø¶¨¹«Ê½µÄϵÊý

µÚÒ»¸ö²»ÓÃÔÚ¸ÄÁË£¬µÚ¶þ¸ö¼ÓÁËÈ¨ÖØ
CODE:
>>  x=x4;y=h4;
w=1./(y+0.00001);
opts=fitoptions('method','NonlinearLeastSquares','Weights',(w).^(1/8),'Lower',[-Inf -Inf -Inf -Inf -Inf  -Inf -Inf],'Upper',[Inf Inf Inf Inf Inf Inf Inf]);
opts.StartPoint= [ 3.7168  -52.5824  110.0003  -66.1606   15.8861  -16.3403    5.6742];
ft_ = fittype('a6*(x^26)+a5*(x^22)+a4*(x^20)+a3*(x^18)+a2*(x^5)+a1*(x^2)+a0','dependent',{'y'},...
    'independent',{'x'},'coefficients',{'a6', 'a5','a4','a3','a2','a1','a0'},'options',opts);
[cf_,good]= fit(x,y,ft_)
plot(x,cf_(x),'or-',x, y, '* ');
legend('ÄâºÏͼ','ԭʼÊý¾Ý')

cf_ =

     General model:
     cf_(x) = a6*(x^26)+a5*(x^22)+a4*(x^20)+a3*(x^18)+a2*(x^5)+a1*(x^2)+a0
     Coefficients (with 95% confidence bounds):
       a6 =       3.132  (2.697, 3.568)
       a5 =      -45.17  (-50.8, -39.54)
       a4 =       95.47  (84.3, 106.6)
       a3 =      -58.04  (-64.36, -51.72)
       a2 =        15.2  (14.57, 15.83)
       a1 =      -16.02  (-16.37, -15.67)
       a0 =       5.646  (5.59, 5.701)

good =

           sse: 4.3743
       rsquare: 0.9945
           dfe: 171
    adjrsquare: 0.9943
          rmse: 0.1599


The more you learn, the more you know, the more you know, and the more you forget. The more you forget, the less you know. So why bother to learn.
5Â¥2011-12-24 11:02:12
ÒÑÔÄ   »Ø¸´´ËÂ¥   ¹Ø×¢TA ¸øTA·¢ÏûÏ¢ ËÍTAºì»¨ TAµÄ»ØÌû

dbb627

ÈÙÓþ°æÖ÷ (ÖøÃûдÊÖ)

¡¾´ð°¸¡¿Ó¦Öú»ØÌû

¸Ðл²ÎÓ룬ӦÖúÖ¸Êý +1
715211229(½ð±Ò+4): ¡ï¡ï¡ï¡ï¡ï×î¼Ñ´ð°¸ àÅ£¬¶àлÁË 2011-12-24 12:40:57
715211229: »ØÌûÖö¥ 2011-12-24 12:41:03
Èç¹ûҪƽ»¬²¿·Ö Îó²îС¿É¸Ä±äÈ¨ÖØ£¬µ«ÊÇ×ÜÊDz»»áÀíÏë
  x=x4;y=h4;
w=1./(y+0.00001);
opts=fitoptions('method','NonlinearLeastSquares','Weights',(w).^(1),'Lower',[0 -Inf 0 -Inf 0  -Inf 0],'Upper',[Inf 0 Inf 0 Inf 0 Inf]);
opts.StartPoint= [ 3.7168  -52.5824  110.0003  -66.1606   15.8861  -16.3403    5.6742];
ft_ = fittype('a6*(x^26)+a5*(x^22)+a4*(x^20)+a3*(x^18)+a2*(x^5)+a1*(x^2)+a0','dependent',{'y'},...
    'independent',{'x'},'coefficients',{'a6', 'a5','a4','a3','a2','a1','a0'},'options',opts);
[cf_,good]= fit(x,y,ft_)
plot(x,cf_(x),'r-',x, y, 'b-');
legend('ÄâºÏͼ','ԭʼÊý¾Ý')

cf_ =

     General model:
     cf_(x) = a6*(x^26)+a5*(x^22)+a4*(x^20)+a3*(x^18)+a2*(x^5)+a1*(x^2)+a0
     Coefficients (with 95% confidence bounds):
       a6 =      0.9442  (0.8139, 1.075)
       a5 =      -15.29  (-17.22, -13.36)
       a4 =       34.43  (30.31, 38.54)
       a3 =      -22.39  (-24.91, -19.87)
       a2 =       10.39  (9.83, 10.94)
       a1 =       -13.1  (-13.56, -12.64)
       a0 =       5.229  (5.102, 5.355)

good =

           sse: 7.3790
       rsquare: 0.9793
           dfe: 171
    adjrsquare: 0.9785
          rmse: 0.2077


The more you learn, the more you know, the more you know, and the more you forget. The more you forget, the less you know. So why bother to learn.
6Â¥2011-12-24 11:28:32
ÒÑÔÄ   »Ø¸´´ËÂ¥   ¹Ø×¢TA ¸øTA·¢ÏûÏ¢ ËÍTAºì»¨ TAµÄ»ØÌû
Ïà¹Ø°æ¿éÌø×ª ÎÒÒª¶©ÔÄÂ¥Ö÷ 715211229 µÄÖ÷Ìâ¸üÐÂ
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