Applying the modeling method of Grey system and accumulated generating operation of reciprocal number for the problem of lower precision as well as lower adaptability in non-equidistant GM (1, 1) model, the calculatio...Applying the modeling method of Grey system and accumulated generating operation of reciprocal number for the problem of lower precision as well as lower adaptability in non-equidistant GM (1, 1) model, the calculation formulas were deduced and a non-equidistant GRM (1, 1) model generated by accumulated generating operation of reciprocal number was put forward .The grey GRM (1, 1) model can be used in non-equal interval & equal interval time series and has the characteristic of high precision as well as high adaptability. Example validates the practicability and reliability of the proposed model.展开更多
Aiming the problem of low accuracy during establishing grey model in which monotonically decreasing sequence data and traditional modeling methods are used, this paper applied the reciprocal accumulated generating and...Aiming the problem of low accuracy during establishing grey model in which monotonically decreasing sequence data and traditional modeling methods are used, this paper applied the reciprocal accumulated generating and the approach optimizing grey derivative which is based on three points to deduce the calculation formulas for model parameters, established grey GRM(1, 1) model based on reciprocal accumulated generating. It provides a new method for the grey modeling. The example validates the practicability and reliability of the proposed model.展开更多
Applying the reciprocal accumulated generating and the reconstruction method of GRM(1,1) model’s background value of non-equidistant sequence based on the exponential trait of grey model and the definition of integra...Applying the reciprocal accumulated generating and the reconstruction method of GRM(1,1) model’s background value of non-equidistant sequence based on the exponential trait of grey model and the definition of integral for the problem of lower precision as well as lower adaptability in non-equidistant GM(1,1) model, the calculation formulas were deduced and a novel non-equidistant GRM(1,1) model generated by reciprocal accumulated generating was put forward. The grey GRM(1,1) model can be used in non-equidistant interval & equidistant interval time series and has the characteristic of high precision as well as high adaptability. Example validates the practicability and reliability of the proposed model.展开更多
In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.B...In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.By mining the geometric features of interval grey number sequences on a two-dimensional surface,all the interval grey numbers are converted into real numbers by means of certain algorithm,and then the prediction model is established based on those real number sequences.The entire process avoids the algebraic operations of grey number,and the prediction problem of interval grey number is usefully solved.Ultimately,through an example＇s program simulation,the validity and practicability of this novel model are verified.展开更多
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 pro...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.展开更多
The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to elimin...The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.展开更多
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...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.展开更多
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 liv...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.展开更多
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 (resear...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.展开更多
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...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.展开更多
By combining conventional grey correlation analysis, grey clustering method and grey forecasting methods with our multi-goal forecast thoughts and the techniques of grey time series processing, we develop six differen...By combining conventional grey correlation analysis, grey clustering method and grey forecasting methods with our multi-goal forecast thoughts and the techniques of grey time series processing, we develop six different grey earthquake forecast models in this paper. Using the record of major earthquakes in Japan from 1872 to 1995, we forecast future earthquakes in Japan. We develop an earthquake forecast model. By using the major earthquakes in Japan from 1872 to 1984, we forecast earthquakes from 1985 to 1995 and check the precision of the grey earthquake models. We find that the grey system theory can be applied to earthquake forecast. We introduce the above analysis methods and give a real example to evaluate and forecast. We also further discuss the problems of how to improve the precision of earthquake forecast and how to strengthen the forecast models in future research.展开更多
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）....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.展开更多
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 init...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.展开更多
The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application Th...The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application This is because the model requires a strong correlation between the system characteristic sequences That reduces the applicability of the model.To solve this problem,this paper proposes a novel multi-variate grey model.This model does not require a certain correlation between system characteristic sequences and has higher applicability Through numerical integration,a two-point trapezoidal formula,and a recursive method,thetime-response expressions ofthetwo model forms are obtained Some properties of the proposed model are further discussed Finally,the validity of the proposed model is evaluated by using two real cases related to China's invention patent development.Theresultsshow that the novel models outperformother models inbothsimulation and prediction applications.展开更多
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 Provinc...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.展开更多
文摘Applying the modeling method of Grey system and accumulated generating operation of reciprocal number for the problem of lower precision as well as lower adaptability in non-equidistant GM (1, 1) model, the calculation formulas were deduced and a non-equidistant GRM (1, 1) model generated by accumulated generating operation of reciprocal number was put forward .The grey GRM (1, 1) model can be used in non-equal interval & equal interval time series and has the characteristic of high precision as well as high adaptability. Example validates the practicability and reliability of the proposed model.
文摘Aiming the problem of low accuracy during establishing grey model in which monotonically decreasing sequence data and traditional modeling methods are used, this paper applied the reciprocal accumulated generating and the approach optimizing grey derivative which is based on three points to deduce the calculation formulas for model parameters, established grey GRM(1, 1) model based on reciprocal accumulated generating. It provides a new method for the grey modeling. The example validates the practicability and reliability of the proposed model.
文摘Applying the reciprocal accumulated generating and the reconstruction method of GRM(1,1) model’s background value of non-equidistant sequence based on the exponential trait of grey model and the definition of integral for the problem of lower precision as well as lower adaptability in non-equidistant GM(1,1) model, the calculation formulas were deduced and a novel non-equidistant GRM(1,1) model generated by reciprocal accumulated generating was put forward. The grey GRM(1,1) model can be used in non-equidistant interval & equidistant interval time series and has the characteristic of high precision as well as high adaptability. Example validates the practicability and reliability of the proposed model.
基金supported by the National Natural Science Foundation of China(7084001290924022)the Ph.D.Thesis Innovation and Excellent Foundation of Nanjing University of Aeronautics and Astronautics(2010)
文摘In grey system theory,the studies in the field of grey prediction model are focused on real number sequences,rather than grey number ones.Hereby,a prediction model based on interval grey number sequences is proposed.By mining the geometric features of interval grey number sequences on a two-dimensional surface,all the interval grey numbers are converted into real numbers by means of certain algorithm,and then the prediction model is established based on those real number sequences.The entire process avoids the algebraic operations of grey number,and the prediction problem of interval grey number is usefully solved.Ultimately,through an example＇s program simulation,the validity and practicability of this novel model are verified.
文摘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.
基金supported by the National Natural Science Foundation of China(71071077)the Ministry of Education Key Project of National Educational Science Planning(DFA090215)+1 种基金China Postdoctoral Science Foundation(20100481137)Funding of Jiangsu Innovation Program for Graduate Education(CXZZ11-0226)
文摘The construction method of background value is improved in the original multi-variable grey model （MGM（1,m）） from its source of construction errors. The MGM（1,m） with optimized background value is used to eliminate the random fluctuations or errors of the observational data of all variables, and the combined prediction model together with the multiple linear regression is established in order to improve the simulation and prediction accuracy of the combined model. Finally, a combined model of the MGM（1,2） with optimized background value and the binary linear regression is constructed by an example. The results show that the model has good effects for simulation and prediction.
基金supported by the National Natural Science Foundation of China (7090103471071077)+2 种基金the National Educational Sciences Planning Key Project of Ministry of Education (DFA090215)the Fundamental Research Funds for the Central Universities (JUSRP21146JUSRP31107)
文摘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.
文摘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.
文摘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.
文摘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.
文摘By combining conventional grey correlation analysis, grey clustering method and grey forecasting methods with our multi-goal forecast thoughts and the techniques of grey time series processing, we develop six different grey earthquake forecast models in this paper. Using the record of major earthquakes in Japan from 1872 to 1995, we forecast future earthquakes in Japan. We develop an earthquake forecast model. By using the major earthquakes in Japan from 1872 to 1984, we forecast earthquakes from 1985 to 1995 and check the precision of the grey earthquake models. We find that the grey system theory can be applied to earthquake forecast. We introduce the above analysis methods and give a real example to evaluate and forecast. We also further discuss the problems of how to improve the precision of earthquake forecast and how to strengthen the forecast models in future research.
文摘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.
文摘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.
基金Supported bythe National Natural Science Foundation of China(71701105)the Major Program of the National Social Science Fund of China(17ZDA092)+1 种基金the Key Research Project of Philosophy and Social Sciences in Universities of Jiangsu Province(2018SJZDI111)Key Projects of Open Topics of Jiangsu Productivity Society in2020(JSSCL2020A004)。
文摘The MGM(1,m,N)model is an effective grey multi-variate forecasting model that considers multiple system characteristic sequences affected by multiplefactors.Nevertheless,it isregularly inaccurate in the application This is because the model requires a strong correlation between the system characteristic sequences That reduces the applicability of the model.To solve this problem,this paper proposes a novel multi-variate grey model.This model does not require a certain correlation between system characteristic sequences and has higher applicability Through numerical integration,a two-point trapezoidal formula,and a recursive method,thetime-response expressions ofthetwo model forms are obtained Some properties of the proposed model are further discussed Finally,the validity of the proposed model is evaluated by using two real cases related to China's invention patent development.Theresultsshow that the novel models outperformother models inbothsimulation and prediction applications.
文摘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.
