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通过考察厚近薄远原则所选用的公式F,可以看出G取值是非常关键的。改变H值可以改变厚近薄远的程度,决定不同时期历史数据的模型误差对预测结果的影响。I值非常小时,将会使较远的... 通过考察厚近薄远原则所选用的公式F ,可以看出G取值是非常关键的。改变H值可以改变厚近薄远的程度,决定不同时期历史数据的模型误差对预测结果的影响。I 值非常小时,将会使较远的模型误差对最终预测结果的影响几乎为零;J 取值越大,其优选的结果越来越靠近于采用远近相同原则的优选结果,换句话说,K 取值越大,厚近薄远的效果越弱。 展开
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2011-08-16 · TA获得超过1.4万个赞
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It could be viewed, through study on Formula F selected by the principel as "giving more weight on the closer one rather than the further", that it is very important as of G value. Change in H value may alter degree/extent(任选) of “weighing more on the closer one than the further”, which does determine impacts of model errors of history datum during periods on predictions. Extremely small I value may lead to impact nearly to zero as of "the further weighing" model error laid on final predictions, while the larger J value gets, the closer the results with optimum seeking method are to that drawn from the principle of "equality between the closer one and the further"; in other words(或:that is,namely), the larger J value gets, the weaker effect as of "weighing more on the closer one than the further" it produces.

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2011-08-16 · TA获得超过282个赞
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Pass to investigate thick near thin far principle choose of formula F, can see a G's taking a value is very decisive.Changing the H value can change thick near thin far degree, decide the model error margin of corresponding period history data not to the influence that predicts a result.The I is very worth a hour, will make the influence of the farther model error margin upon the end estimate result almost to zero;The J takes a value more big, the result of its optimization more and more close to in adoption far near same principle of optimization result, in other words, the K takes to be worth more big, thick near thin far of the effect is more weak.
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xx谢谢你
2011-08-13 · 超过13用户采纳过TA的回答
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By investigating the thick BoYuan principle for the use of nearly formula, it can be seen that the G F values are very key change H value can change near the extent of the BoYuan thick, decided to different period of historical data model for prediction error influence on the result of the I value very hour, will make far away on final prediction model error influence on the result of the almost to zero; The greater the value, the J
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