| ²é¿´: 4286 | »Ø¸´: 3 | |||
| µ±Ç°Ö»ÏÔʾÂú×ãÖ¸¶¨Ìõ¼þµÄ»ØÌû£¬µã»÷ÕâÀï²é¿´±¾»°ÌâµÄËùÓлØÌû | |||
»ÒÉ«Áµ·ãгæ (СÓÐÃûÆø)
|
[½»Á÷]
Çó¾ùÔÈ£¨×îÓÅ£©À¶¡³¬Á¢·½ÊµÑéÉè¼ÆµÄmatlab³ÌÐò£¡£¡ ÒÑÓÐ3È˲ÎÓë
|
||
|
±¾È˼±Ðè¾ùÔÈ£¨×îÓÅ£©À¶¡³¬Á¢·½ÊµÑéÉè¼ÆµÄmatlab³ÌÐò£¬Çë³æÓÑÃǰïæ£¬¸Ð¼¤²»¾¡£¡£¡ [ ·¢×ÔÊÖ»ú°æ http://muchong.com/3g ] |
» ²ÂÄãϲ»¶
Ò»Ö¾Ô¸085502£¬267·ÖÇóµ÷¼Á
ÒѾÓÐ16È˻ظ´
085801µçÆø×¨Ë¶272Çóµ÷¼Á
ÒѾÓÐ3È˻ظ´
366Çóµ÷¼Á
ÒѾÓÐ9È˻ظ´
²ÄÁϹ¤³Ì085601£¬270Çóµ÷¼Á
ÒѾÓÐ37È˻ظ´
279ѧ˶ʳƷרҵÇóµ÷¼ÁԺУ
ÒѾÓÐ18È˻ظ´
290µ÷¼ÁÉúÎï0860
ÒѾÓÐ31È˻ظ´
Ò»Ö¾Ô¸085802 323·ÖÇóµ÷¼Á
ÒѾÓÐ13È˻ظ´
277Çóµ÷¼Á
ÒѾÓÐ23È˻ظ´
322Çóµ÷¼Á£¬08¹¤¿Æ
ÒѾÓÐ4È˻ظ´
²ÄÁϹ¤³Ì281»¹Óе÷¼Á»ú»áÂð
ÒѾÓÐ30È˻ظ´
°Ë½ä¾ÈÃü
гæ (СÓÐÃûÆø)
- Ó¦Öú: 0 (Ó×¶ùÔ°)
- ½ð±Ò: 551.7
- É¢½ð: 20
- Ìû×Ó: 90
- ÔÚÏß: 4.1Сʱ
- ³æºÅ: 6604942
- ×¢²á: 2017-05-25
- ÐÔ±ð: MM
- רҵ: µç»úÓëµçÆ÷
4Â¥2021-08-23 17:57:52
Åà¸ù¼ÓÓÍÌõ
½ð³æ (³õÈëÎÄ̳)
- Ó¦Öú: 0 (Ó×¶ùÔ°)
- ½ð±Ò: 481.6
- Ìû×Ó: 5
- ÔÚÏß: 7Сʱ
- ³æºÅ: 5593495
- ×¢²á: 2017-02-16
- ÐÔ±ð: GG
- רҵ: »úе½á¹¹Ç¿¶Èѧ
¡ï ¡ï
Сľ³æ: ½ð±Ò+0.5, ¸ø¸öºì°ü£¬Ð»Ð»»ØÌû
jjdg: ½ð±Ò+1, ¸Ðл²ÎÓë 2017-07-26 11:29:03
Сľ³æ: ½ð±Ò+0.5, ¸ø¸öºì°ü£¬Ð»Ð»»ØÌû
jjdg: ½ð±Ò+1, ¸Ðл²ÎÓë 2017-07-26 11:29:03
|
LHSDESIGN Generate a latin hypercube sample. X=LHSDESIGN(N,P) generates a latin hypercube sample X containing N values on each of P variables. For each column, the N values are randomly distributed with one from each interval (0,1/N), (1/N,2/N), ..., (1-1/N,1), and they are randomly permuted. X=LHSDESIGN(...,'PARAM1',val1,'PARAM2',val2,...) specifies parameter name/value pairs to control the sample generation. Valid parameters are the following: Parameter Value 'smooth' 'on' (the default) to produce points as above, or 'off' to produces points at the midpoints of the above intervals: .5/N, 1.5/N, ..., 1-.5/N. 'iterations' The maximum number of iterations to perform in an attempt to improve the design (default=5) 'criterion' The criterion to use to measure design improvement, chosen from 'maximin' (the default) to maximize the minimum distance between points, 'correlation' to reduce correlation, or 'none' to do no iteration. Latin hypercube designs are useful when you need a sample that is random but that is guaranteed to be relatively uniformly distributed over each dimension. |
2Â¥2017-07-26 09:50:50
Mr__Right
ר¼Ò¹ËÎÊ (ÖøÃûдÊÖ)
-

ר¼Ò¾Ñé: +31 - Ó¦Öú: 317 (´óѧÉú)
- ½ð±Ò: 14456.3
- É¢½ð: 500
- ºì»¨: 54
- Ìû×Ó: 2716
- ÔÚÏß: 950.6Сʱ
- ³æºÅ: 1972612
- ×¢²á: 2012-09-04
- ÐÔ±ð: GG
- רҵ: Ó¦ÓÃÊýѧ·½·¨
- ¹ÜϽ: ³ÌÐòÓïÑÔ
¡ï ¡ï ¡ï
Сľ³æ: ½ð±Ò+0.5, ¸ø¸öºì°ü£¬Ð»Ð»»ØÌû
jjdg: ½ð±Ò+2, ¸Ðл²ÎÓë 2017-07-26 11:29:12
Сľ³æ: ½ð±Ò+0.5, ¸ø¸öºì°ü£¬Ð»Ð»»ØÌû
jjdg: ½ð±Ò+2, ¸Ðл²ÎÓë 2017-07-26 11:29:12

3Â¥2017-07-26 10:18:03













»Ø¸´´ËÂ¥
5