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.

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.

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.

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。

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。

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.

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.

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.

A Grey Prediction Model on Vibration Severity Development of a Pump

The method to enhance the precis io n of a grey model GM (1, 1) for predicting the development of vibration severity of a pump is investigated. The rectifying procedures involve the structure and the parameters regarding GM(1,1). A new model based on GM(1, 1), which is GM (E,1,1), is proposed. In GM(E,1,1), the distribution of relative errors rati os between the original series and predicting series obtained by the mean of GM( 1,1) are considered in special points to set up the threshold and adjusting coef ficients to control the modified action and the rectified amount based on distri bution of the original series. The case shows that GM(E, 1, 1) is good at predic ting the vibration severity development of the pump.

水工隧洞建设对区域水资源优化的影响

随着人口不断攀升及工商业的发展,区域用水需求量逐年增加,使得水资源短缺问题日显严重,水工隧洞成为目前区域性水资源嫁接渠道,日益成为研究焦点。本文首先利用灰色系统之灰关联分析法(Grey relational analysis)评估区域水资源优化,以得知水工隧洞建设的影响值;另以灰色系统之GM(1,N)模型对水工隧洞建设的影响值进行模拟预测;最后对实际值与模拟预测值进行相对残差值评析,并进一步提出一种预测效能最优的分析方法。

Forecast of Maize Production in Henan Province

Considering the influence of meteorological factors on maize production, in order to improve the yield of maize in Henan Province, a grey combination model is constructed to predict the yield of maize in Henan Province. Firstly, the yield of maize in 2017 is obtained by GM (1, 1) model;secondly, the trend yield of maize is obtained by HP filter method, then the meteorological yield of maize is obtained, and the yield of maize reduction is determined according to the meteorological yield. Combined with Markov model, the maize yield reduction in various cities in Henan Province is forecasted. Finally, based on the reduction of production, policy recommendations are made for maize production in Henan Province.

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.

Analyzing China’s OFDI using a novel multivariate grey prediction model with Fourier series

Purpose–With the development of economy,China’s OFDI constantly increase in recent year.Meanwhile,OFDI hasspillovereffectoneconomicdevelopmentandtechnologicaldevelopmentofhomecountry.Thus,accurateOFDI prediction is a prerequisite for the effective development of international investment strategies.The purpose of this paper is to predict China’s OFDI accurately using a novel multivariable grey prediction model with Fourier series.Design/methodology/approach–This paper applied a multivariable grey prediction model,GM(1,N),to forecast China’s OFDI.In order to improve the prediction accuracy and without changing local characteristics of grey model prediction,this paper proposed a novel grey prediction model to improve the performance of the traditionalGM(1,N)modelbycombiningwithresidualmodificationmodelusingGM(1,1)modelandFourierseries.Findings–The coefficients indicate that the export and GDP have positive influence on China’s OFDI,and,according to the prediction result,China’s OFDI shows a growing trend in next five years.Originality/value–This paper proposed an effective multivariable grey prediction model that combined the traditionalGM(1,N)modelwitharesidualmodificationmodelinordertopredictChina’sOFDI.Accurateforecasting of OFDI provides reference for the Chinese Government to implement international investment strategies.