The Modified GM( 1 , 1) Grey Forecast Model

Because the impacts of the factors such as some disturbances are graduallyadded into the system, the grey forecast results will deviate from the systemtrue value. To improve the forecast precision, Pro-Dens Julons provided twomethfor-But they had not consider the impact of artificial disturbance. LiZhihua et al. of Qinghua Univ. presented another method. This paper revisesthe method and make it be a spocial case.

Forecast Grain “Three Quantities” Based on Grey GM (1, 1) and Promote the Structural Reform of Grain Supply Side

As a special product, the cultivation and production of grain directly affect the consumption of people, which has an important influence on the development of social economy and the national economy and people’s livelihood. Firstly, the present situation of grain production is analyzed, and the problems facing the structural reform of grain supply side in China are analyzed from grain output and its import and export volume. Secondly, we use grey GM (1, 1) model to predict grain output and consumption, grain import and export volume and all kinds of grain crops output in China, and then analyze the future trend of grain production in China. Finally, we put forward construction of grain branding, rational allocation of grain planting varieties, construction of traceability system for grain production, further grain processing and development of “Internet agriculture” industrial model to promote structural reform of grain supply side.

Predicting the Number of Beijing Science and Technology Personnel Based on GM(1,N) Model

In this paper, based on the Science and Technology Statistics in Beijing Statistical Yearbook, grey theory is used to study the relationship among S&T (Science and Technology) activities personnel, R&D (research and development) personnel FTE (Full Time Equivalent), intramural expenditure for R&D and Patent Application Amount. According to the grey correlation coefficient, screening of grey GM(1,N) prediction variables, the grey prediction model is established. Meanwhile, time series model and GM(1,1) model are established for patent applications and R&D personnel equivalent FTE. By comparing the simulating results with the real data, the absolute relative error of prediction models is less than 10%. The results of the prediction model are tested. In order to improve the prediction accuracy, the mean values of the predicted values of the two models are brought into the GM(1,N) model to predict the number of scientific and technical personnel in Beijing during 2015-2025. Forecast results show that the number of science and technology personnel in Beijing will grow with exponential growth trend in the next ten years, which has a certain reference value for predicting the science and technology activities and formulating the policy in Beijing.

灰色GM(1,l)和Verhulst模型在吹填土地基沉降中的应用

在利用灰色GM(1,l)和Verhulst模型预测真空预压加固吹填土地基的最终沉降量时,建模序列直接影响预测结果的精度。结合某吹填土地基加固工程的沉降监测数据,探讨监测序列长度、建模序列长度对上述2种模型最终沉降量预测值及预测精度的影响,总结出不同模型预测地基最终沉降量时建模序列的选取规律。研究结果表明,上述2种模型预测地基最终沉降量的误差均小于1.0%,灰色GM(1,l)模型的适应性更好。

灰色GM~*(1,l)模型的性质及其应用

灰色GM（l，l）模对生态预测有重要应用，本文讨论了它的一个改进模GM*（l，1），并深化了文[l]提出的两个问题，给出了较简明的证法，还确定了文[1]所希望的一个“合适的”常数．

Improved unequal interval grey model and its applications

A new method to improve prediction precision of GM（1,1） model with unequal time interval is presented.The grey derivative is multiplied by a parameter to guarantee the time response function satisfying approximately exponential function distribution.To simplify the process of parametric estimation,an approximate value is taken for the multiplied parameter.Then the estimators of coefficient of development and grey action quantity can be derived.At the same time,the principle of the new information priority is also considered.We take the last item of the first-order accumulated generation operator（1-AGO） on raw data sequence as the initial condition in the time response function.Then the new information can be taken full advantage of through the improved initial condition.Some properties of this new model are also discussed.The presented method is actually a combination of improvement of grey derivative and improvement of the initial condition.The results of an example indicate that the proposed method can improve prediction precision prominently.

优化背景值的GM(1,1)

为了提高模型的拟合精度,提出了一种新的改进GM(1,1)模型.从优化GM(1,1)模型背景值的定义出发,推导出利用原始数据生成的背景值公式,将其与经过优化的初始条件结合,构造出改进的GM(1,1)模型.此模型将在很大程度上消除由于背景值的选取所产生的误差.对该模型进行数据模拟,通过与原模型中数据的比较、分析,验证出新的优化模型具有更好的模拟精度,说明该模型的有效性,可以将其应用于对其它数据的拟合预测.

江苏省艾滋病、淋病和梅毒发病率GM(1,1)灰色模型预测研究

目的:探析GM(1,1)灰色模型预测江苏省艾滋病、淋病和梅毒发病率的适用性,并评价预测效果。方法:运用GM(1,1)建模方法分别对2003-2009年间江苏省艾滋病、淋病和梅毒的发病率进行模型拟合,对拟合精度进行评判和相应修正,并运用论证后的GM(1,1)模型进行梅毒发病率预测。结果:江苏省艾滋病和淋病发病率不适合用GM(1,1)模型进行预测,梅毒发病率的GM(1,1)模型拟合精度和预测效果较好,可进行短期预测,且预测提示江苏省梅毒发病率在今后几年仍将呈上升趋势。结论:增加原始数据的平滑度、减弱极端值的影响以及正确选择建模择数据段是提高GM(1,1)模型预测艾滋病、性传播疾病发病率适用性的重要途径。

隧道围岩变形预测的GM(1,1)模型优化分析

基于灰色理论的GM(1,1)模型对隧道围岩变形进行短期预测,研究结果表明,隧道围岩变形差值数列的光滑性比累计变形数列的光滑性好,用围岩位移变形差值数列作为原始数列,预测精度更高。

基于新型核与灰度序列的时滞GM(1,N)模型及其应用

为了解决GM(1,N)模型在新型核与灰度的基础上,对驱动项的延迟作用机理不明确的问题,将时滞参数引入到GM(1,N)模型的驱动项中,构建了基于新型核与灰度的时滞GM(1,N)模型,分析了时滞参数的辨识方法,讨论了新模型的建模机理。为了更好地对该模型的有效性进行验证,将优化的时滞GM(1,N)模型对南京市的雾霾进行预测分析,选择GM(1,N)模型、一元回归模型与文中的优化模型进行对比。结果显示,优化模型对PM10浓度的拟合精度更高,且误差均控制在5%之内,从而验证了提出的优化模型适用于具有时滞特征数据的模拟和预测。

应用灰色动态GM(1,1)数学模型进行临床血液采集量预测

目的探讨应用灰色动态 GM（1，1）模型，分析和预测常态下承德市中心血站血液品种采集数量的动态发展变化趋势，根据模型的应用效果做出定量预测。方法根据承德市中心血站2004年1月～2013年12月的全血（400 ml）（人次）、单采少白血小板（人份）血液品种年采集数据，将2013年预测值与实际值比较，检验模型的预测能力，同时分析2014～2016年血液采集数量。结果以上两类血液采集品种数量灰色动态 GM（1，1）模型的 Y（t）后验差比（均方差）C均＜0.35，小误差概率P值均为1。精度均为优，用于血液采集量预测的效果好。结论承德市中心血站以上两类血液采集品种数量呈逐渐增高趋势。灰色系统一阶模型 GM（1，1）作为一种新型预测模型，能够在常态下合理预测采供血系统血液采集量。

The softening prediction of HSLA steel heat-affected zone based on the grey system

The high-strength low-alloy（ HSLA ） steel heat-affected zone （HAZ）softening was predicted using a grey model. HSLA steel DILLIMAX690E, NK-HITEN61OU2 and BHW35 were taken as examples in the research on ultra-narrow gap automatic welding technology. Test results turned out to be that the errors between the values calculated by the Grey Model （GM） （ 1,1 ） model and their actual value were less than 2%, indicating that the grey prediction method could accurately reflect the actual situation of the high-strength low-alloy steel heat-affected zone softening. This method will play a crucial role in guiding the applications of HSLA steel welded structures in the future.

Grey forewarning and prediction for mine water inflowing catastrophe periods

Based on the theory of grey system, established GM （1, 1） grey catastrophe predict model for the first time in order to forecast the catastrophe periods of mine water inflowing （not the volume of water inflowing）. After establishing the grey predict system of the catastrophe regularity of 10 month-average volume of water inflowing, the grey forewarning for mine water inflowing catastrophe periods was established which was used to analyze water disaster in 400 meter level of Wennan Colliery. Based on residual analysis, it shows that the result of grey predict system is almost close to the actual value. And the scene actual result also shows the reliability of prediction. Both the theoretical analysis and the scene actual result indicate feasibility and reliability of the method of grey catastrophe predict system.

Prediction of the maximum water inflow in Pingdingshan No.8 mine based on grey system theory

In order to prevent and control the water inflow of mines, this paper built a new initial GM（1, 1） model to torecast the maximum water inflow according to the principle of new information. The effect of the new initial GM（1, 1） model is not ideal by the concrete example. Then according to the principle of making the sum of the squares of the difference between the calculated sequences and the original sequences, an optimized GM（1, I） model was established. The result shows that this method is a new prediction method which can predict the maximum water inflow accurately. It not only conforms to the guide- line of prevention primarily, but also provides reference standards to managers on making prevention measures.

Urgency and Necessity on Adjustment of China’s Current Agricultural Structure Based on the Stability and Developmental Trend Analyses of Pork Yield in China

With the development of economy, meat gradually plays an important role in Chinese people’s dietary pattern. As the most direct reflection of agricultural system, food system has always been the main output of agricultural system, and pork has occupied an important position in Chinese food system. We attempts to find the systematical disorder of current agricultural system by analyzing the meat output of the agricultural system. H-P Filter and Grey Prediction GM(1,1) Model was adopted to explore the inner rules between pork production and agricultural system in China. The results indicated that pork consumption ratio in Chinese urban residents’ dietary pattern constantly kept about 6%, the growth potential of grain yield is limited while the growth potential of pork yield is increased in China. By Grey Prediction GM(1,1) Model, we predicted the pork yield would reach 59.07 Mt in 2020, 110.25 Mt in 2060, 205.78 Mt in 2100, the demand of feed would reach 177.22 Mt in 2020, 330.75 Mt in 2060, 617.34 Mt in 2100. In China, agricultural system is traditional “pork-grain” mode, feed has been one of the biggest section that consumed grain. The present “pork-grain” agricultural system cannot meet the huge demand of grain from feed, adjusting the agricultural structure is imperative. Reforming the current agricultural system into grassland agricultural system which takes the beef and mutton as predominates would be a good choice for China in the future.

基于灰色小波的网络流量组合预测模型

为了更准确的预测网络流量和刻画流量特性,提出了一种基于小波变换理论与灰色理论的组合预测方法。该方法拟合了小波分解的平稳化处理优点和灰色预测中的平移处理优点,根据提出的预测方法建立了基于灰色小波的网络流量预测模型。首先对分解后的时间序列分别进行平移预处理,然后对预处理后的序列数据进行预测并重构,从而得到原始时间序列的预测值。对实际的采集数据进行仿真实验,仿真结果表明,该方法预测效果良好,优于一般小波预测方法。

多项式分布滞后模型在桥梁挠度预测中的应用

介绍了PDL(多项式分布滞后)模型,并将其应用于某桥梁挠度预测,重点考虑了温度以及车流量对挠度的影响。借助EVIEWS软件对桥梁不同时期的挠度变形值进行预测,并与灰色GM(1,1)模型的预测结果进行对比分析。结果表明,PDL模型具有比灰色模型更高的预测精度,其预测结果更为可靠,对类似工程有一定的借鉴作用。

水质的评价和预测模型

本文首先考虑到水质类别的差异和相同类别水质在数量上的差异对综合评价的影响,构造"S"形的变权函数,对属于不同水质类别的同种污染指标进行"动态加权",建立基于逼近理想点排序法的评价模型和利用灰色关联度的分析方法,对长江水质状况做出了综合评价;其次,根据7个观测站的位置将干流分成8段,把每段河道内所有污染源都等效为一个段中央的连续稳定源,分别利用稳态条件下的一维水质模型及质量守恒定律,得出中间6段每个月的排污量,综合比较各河段一年多来的总排污量得到主要污染源的分布区域;然后,用每年不可饮用类水的百分比之和刻画水质状况,综合利用灰色GM(1,1)模型和时间序列分折方法,对变化趋势进行了预测;最后,建立不可饮用类水的百分比与长江水总流量和废水排放量的线性回归模型,计算在满足约束条件下排污量的极限值,用排污量的预测值减去极限值,得到未来10年的污水处理量。

新疆水资源生态足迹核算与预测

根据水资源生态足迹的基本原理和计算模型,引入水资源负载指数,对新疆2005—2014年水资源生态足迹、水资源生态承载力进行计算,并运用灰色预测模型GM(1,1)对2015—2025年的生态赤字/盈余趋势进行预测。结果表明:(1)新疆历年水资源生态足迹大于水资源承载力,处于生态赤字状态,从2005年的-7.83×10~7hm^2下降至2013年的-9.06×10~7hm^2,水资源开发率很低;(2)2005—2014年新疆水资源生态足迹和承载力均呈上升趋势,人均生态足迹和人均承载力呈上下波动状态,生产用水生态足迹在三个水资源账户中比例最大,远远超出其它两部分,占总水资源足迹的95.86%;(3)水资源负载指数总体呈上升趋势,表明水资源的利用程度逐渐加强,2005—2012年负载指数在2~5之间,表明新疆水资源利用程度中等;2013—2014年负载指数在5~10之间,表明新疆水资源利用程度高,开发条件困难;(4)新疆水资源存在分布不均匀的状态,南疆、北疆、东疆差异较大,南疆、北疆水资源生态足迹、水资源承载力均大于东疆,而南、北疆万元GDP水资源生态足迹则小于东疆;(5)对2015—2025年水资源进行预测,新疆水资源一直处于生态赤字状态,而且水资源生态赤字呈逐年减小的趋势,水资源生态赤字越来越严重,今后的形势越来越严峻,在利用中提高节水意识。

振荡型GM(1,1,k)幂模型的构建及其应用

针对含有时间趋势性和振荡性的小样本序列的建模预测问题,提出了同时包含时间延迟参数、时间作用参数及多项式的振荡型GM(1,1,k)幂模型,采用遗传算法寻找模型中的最优非线性参数,提高了模型的预测精度。将该模型应用于我国季度风电产量的预测,结果显示,振荡型GM(1,1,k)幂模型具有良好的预测性能,为含有时间趋势性的小样本振荡序列预测提供了一种有效的建模方法和预测手段。