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general grey model
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  “general grey model”译为未确定词的双语例句
     The general grey model does not work normally when observation data is insufficient and mutual effect or interrelation between variables exists.
     当观测资料的数据量少,而又存在多个相互影响或关联的变量时,常用的灰色预测模型GM(1,1)不能全面考虑多个变量。
短句来源
     The general grey model GM(1,1)can not take multi variables into account overall in forecast problems which have some variables relating with each other and few observational data available.
     当观测资料的数据量少而又存在多个相互影响或关联的变量时,常用的灰色预测模型GM(1,1)不能全面考虑多个变量。
短句来源
     The general grey model GM (1,1) cannot take multi variables into account in forecast problems with several variables relating with each other and few observation data available.
     当观测资料的数据量少,而又存在多个相互影响或关联的变量时,常用的灰色预测模型GM(1,1)不能全面考虑多个变量。
短句来源
     The general grey model doesn't work normally when observation data is insufficient and mutual effect or interrelation exists between variables.
     当观测资料的数据量少而又存在多个相互影响或关联的变量时,常用的灰色GM(1,1)模型不能全面考虑多个变量,GM(1,n)模型也不能考虑相互影响问题,而采用MGM(1,n)模型,较好地解决了这一问题。
短句来源
  相似匹配句对
     general;
     (2)总论;
短句来源
     In general,L.
     L.
短句来源
     The General Grey DEA Model
     一般灰色DEA模型
短句来源
     It is an expansion of general interval grey number.
     它是一般区间灰数的延伸。
短句来源
     The Operation and its Nature of General Grey Function Limit
     泛灰函数极限的运算与性质
短句来源
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The general grey model for load prediction in power systems is improved by introducing two adjustable parameters so as to turn it into an adjustable grey prediction model. The restrictions against setting up the model are decreased and the scope of application is more wide-spread. The results of prediction are controllable and adjustable, thus improving the accuracy of prediction.For comparison, four prediction methods, including the adjustable grey model are used to predict...

The general grey model for load prediction in power systems is improved by introducing two adjustable parameters so as to turn it into an adjustable grey prediction model. The restrictions against setting up the model are decreased and the scope of application is more wide-spread. The results of prediction are controllable and adjustable, thus improving the accuracy of prediction.For comparison, four prediction methods, including the adjustable grey model are used to predict the power load of Wuxi city, Jiangsu Province. The adjustable grey prediction model proves to be more practical.

本文对电力系统负荷预测的普通灰色模型进行了可调性改进,成为可调灰色预测模型,减少了建模的限制条件,应用范围更加广泛,可以控制、调整预测结果,使精度提高。文中对江苏省无锡市电力负荷使用四种预测方法比较,从理论和应用两方面证实了可调灰色模型明显的实用性。

The system of urban garbage quantity is a grey system.The quantity of garbage produced in the future in urban area can be predicted by using large amount of grey information contained in the system and comformable grey model based on the principle of grey controlling system.Taking Shanghai municipality for example the manuscript has established a grey model to predict urban garbage quantity.The predictive precision of this model is in a good state according to con- cerned standards.The prediction for the garbage...

The system of urban garbage quantity is a grey system.The quantity of garbage produced in the future in urban area can be predicted by using large amount of grey information contained in the system and comformable grey model based on the principle of grey controlling system.Taking Shanghai municipality for example the manuscript has established a grey model to predict urban garbage quantity.The predictive precision of this model is in a good state according to con- cerned standards.The prediction for the garbage quantity produced in the future in Shanghai shows that the predctive val- ues of intermediate to short-terns(1990 to 2000 your)actually are relatively exact.Because of simple calculation and good verification for the forecast values,the grey model can provide valuable data for the environment control and city plan and supply a reliable basis for the treatment of urban garbage.The grey model mentioned herein is mainly used to predict a normal trend without sudden changes.In order to raise the forecast accuracy and reflect the sudden influences, the general grey model(1,1)and forecast model of sudden changes could be combined,thus it can reflect the future posi- tion.The manuscript points out that the key to control urban garbage quantity is to control the urban population increase, and the scale and space of garbage treatment system should be suitable to the economic development and the selection of garbege site is important to improve ecological environment and to prevent environmental pollution.

作者采用灰色控制系统理论进行城市垃圾量的预测,经验证其中近期预测值是接近实际的,具有一定的实用价值。

The general grey model does not work normally when observation data is insufficient and mutual effect or interrelation between variables exists.A self-adapting namely MGM(1,n) model,which is an extension of the GM(1,1) model for n-variable,is introduced to solve the problem.The principle of variable selection,establishment of differential equations for n-variable,deduction of time-response function for solving the variables as well as the statistical tests of the model are give in detatiled.The...

The general grey model does not work normally when observation data is insufficient and mutual effect or interrelation between variables exists.A self-adapting namely MGM(1,n) model,which is an extension of the GM(1,1) model for n-variable,is introduced to solve the problem.The principle of variable selection,establishment of differential equations for n-variable,deduction of time-response function for solving the variables as well as the statistical tests of the model are give in detatiled.The validity of the method is demonstrated by calculating the observation data of an earth dam.It verifies that the model can reflect the mutual effect between multiple variables and attains the best forecasting.

当观测资料的数据量少,而又存在多个相互影响或关联的变量时,常用的灰色预测模型GM(1,1)不能全面考虑多个变量。本文采用自适应MGM(1,n)模型———多变量灰色预测模型,较好地解决了这一问题。MGM(1,n)模型是GM(1,1)模型在,n元多变量情况下的推广,其参数能够反映实际工程或社会系统中多个变量间的相互影响、相互制约的关系。内容包括:建模变量的选择,建立n元微分方程组,求解变量的时间响应函数和模型检验。通过对某土石坝观测资料的计算,表明这一方法是可行和有效的。对比其他几个模型.如GM(1,1)等,MGM(1,n)模型能反映出变量间的相互影响,从而获得较好的预测效果。

 
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