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ÕæÇ¿±ØÊ¤: ·ÇÓ¦Öú£¬ÇëÎðµã»÷Ó¦Öú 2014-09-17 08:39:55
ÕæÇ¿±ØÊ¤: Çë˽ÐÅÉÌÒ飬¾¯¸æ¹ã¸æÐû´« 2014-09-17 08:40:28
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¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ¡ï ...
ÕæÇ¿±ØÊ¤: ½ð±Ò+3, лл 2014-09-17 08:40:44
MASc-girl: ½ð±Ò+50, ·­ÒëEPI+1, ¡ï¡ï¡ï¡ï¡ï×î¼Ñ´ð°¸ 2014-09-17 08:47:48
As can be seen by the values of RD and ARD in tables 1 and 2, the best results were obtained with Apelblat equation, followed by empirical polynomial equation and ¦Ëh equation. Therefore, Apelblat equation was more suitable for the study system and the temperature range used in this paper. Relatively speaking, all the correlation coefficients R2 obtained with Apelblat equations were above 0.99, with the average relative error (ARD) less than 4% and the maximum root mean square deviation (105RSMD) of 27.56. Similarly, all the correlation coefficients R2 obtained with experience polynomial equation were also above 0.99, with the average relative error (ARD) less than 4% and the maximum root mean square deviation (105RSMD) was 48.16. However, all the correlation coefficients R2 obtained with ¦Ëh equations were above 0.91, with the average relative error (ARD) less than 18% and the maximum root mean square deviation (105RSMD) was 84.73. Figure 1-12 showed a more straightforward results of the individual equations.
The Data calculated with Apelblat equation fitting and the experimental data were compared as follows:
3Â¥2014-09-16 23:42:39
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