Chaoqing Yuan, Yuxin Zhu, Ding Chen, Sifeng Liu and Zhigeng Fang
The purpose of this paper is to compare GM(1,1) model, rolling GM(1,1) model and metabolism GM(1,1) model included in the GM(1,1) model cluster and use these models to forecast…
Abstract
Purpose
The purpose of this paper is to compare GM(1,1) model, rolling GM(1,1) model and metabolism GM(1,1) model included in the GM(1,1) model cluster and use these models to forecast global oil consumption.
Design/methodology/approach
Simulated sequences will be generated randomly, and used to test the models included in the GM(1,1) model cluster; and these grey forecasting models are applied to forecast global oil consumption.
Findings
Effectiveness of these grey forecasting models is proved by random experiments, which explains the model adaptability. Global oil consumption is predicted, and it shows that global oil consumption will increase at a rather big growth rate in the next years.
Originality/value
The effectiveness of medium-term prediction of these grey forecasting models is analyzed by random experiments. These models are compared, and some basis for model selection is obtained.
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The purpose of this paper is to investigate the effectiveness of GM(1,1) model on linear growth sequences (LGS) by random experiments and global primary energy consumption is…
Abstract
Purpose
The purpose of this paper is to investigate the effectiveness of GM(1,1) model on linear growth sequences (LGS) by random experiments and global primary energy consumption is predicted as by the GM(1,1) and the autoregressive integrated moving average (ARIMA) model, which is used as a reference.
Design/methodology/approach
LGS generated randomly are used for GM(1,1) modeling. The results of the massive repeated random experiments are analyzed to test the effectiveness of the GM(1,1) model and global primary energy consumption is predicted using the GM(1,1) model and the ARIMA model.
Findings
The use of the GM(1,1) model is effective when used for a LGS and the model is proven to be reliable by the experiments. Global primary energy consumption is predicted with the GM(1,1) model and the ARIMA model as a case study, and the results show that GM(1,1) is quite good. Global primary energy consumption will increase by 1.03 percent in 2016.
Originality/value
The contribution of this paper includes the following: first, the applicability of the GM (1,1) model is further discussed with random experiments and it is feasible for a LGS; second, random experiments provide good proof that four data are enough for GM(1,1) modeling, and GM(1,1) model is reliable; third, prediction by using GM(1,1) model with small data is even better than time-series analysis in the case study.
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Wenfeng Yuan, Sifeng Liu and Chaoqing Yuan
The paper attempts to establish a two‐dimension frame to analyze dynamic supplier risks of large‐scale and complex equipment and study the probability distribution of the…
Abstract
Purpose
The paper attempts to establish a two‐dimension frame to analyze dynamic supplier risks of large‐scale and complex equipment and study the probability distribution of the occurring risks.
Design/methodology/approach
Starting from the dynamic and correlated supplier risks of large‐scale and complex equipment, a two‐dimension frame to analyze these risks is established. A maximum entropy model is also built to research the probability distribution of the risks; then, K‐T conditions are proved to solve the model. A real case is also studied in the last part of the paper.
Findings
The results are convincing: in order to analyze the supplier risk dynamically of large‐scale and complex equipment development project, a two‐dimension analysis frame is established and a maximum entropy model is worked out. The case study shows that they are valuable.
Practical implications
The two‐dimension frame gives a new viewpoint for risk management, but also the maximum entropy model supplies a valuable method for risk management.
Originality/value
The paper succeeds in creating a dynamic analysis frame to study risks and building a new method to research the disciplines of the dynamic risks.
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Chaoqing Yuan, Dejin Song, Benhai Guo and Naiming Xie
The purpose of this paper is to attempt to analyze the situation and trend of China's energy consumption structure and predict it.
Abstract
Purpose
The purpose of this paper is to attempt to analyze the situation and trend of China's energy consumption structure and predict it.
Design/methodology/approach
Starting from the situation of China's energy consumption structure, a quadratic programming model is created to analyze the trend of it. A homogeneous Markov chain is chosen to predict China's energy consumption structure with the data collected from China's Statistical Yearbook. Finally, the implication of the prediction is explained.
Findings
The results are convincing: the substitution of different energies are found, China will not enter the oil era, natural gas and non‐fossil energy will rapidly develop.
Practical implications
The results of this article can provide an important basis for the government to make a non‐fossil energy development plan and energy policies.
Originality/value
The paper succeeds in revealing and predicting China's energy consumption structure by quadratic programming and homogeneous Markov chain.
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Jie Cui, Naiming Xie, Hongyan Ma, Hong liang Hu, Zhengya Yang and Chaoqing Yuan
– The purpose of this paper is to study the properties of derived grey verhulst prediction model with multiplication transformation and reduce its modeling complexity.
Abstract
Purpose
The purpose of this paper is to study the properties of derived grey verhulst prediction model with multiplication transformation and reduce its modeling complexity.
Design/methodology/approach
The paper discussed the parameter characteristics of grey derived verhulst model under multiple transformation, and demonstrated its effect on its simulative value and predictive value by investigating the multiple transformation acting on the raw data sequence of this grey model. The parameter characteristics of this model under multiple transformations and its effect of the simulation value and forecasting value are analyzed by studying the properties of multiply transformation of this model.
Findings
The research finding shows that the modeling accuracy of derived grey verhulst model is in no relation to multiple transformations.
Practical implications
The above results imply that the data level can be reduced; the process of building derived grey verhulst model can be simplified; but the simulative and predictive accuracy of this model remain unchanged.
Originality/value
The paper succeeds in realising the properties of derived grey verhulst model by using the method of multiplication transformation, which is helpful to understand the modeling mechanism and expand the application range of derived grey verhulst model.
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Hongqi Liu, Tianbing Jia, Chaoqing Yuan and Yifan Zhang
This paper attempts to provide novel approaches and tools for the analysis and measurement of stock bubbles.
Abstract
Purpose
This paper attempts to provide novel approaches and tools for the analysis and measurement of stock bubbles.
Design/methodology/approach
The study is based on the perspective of a generalized virtual economy and the circulation process of accumulation strengthening and exclusion in the stock noise and is based on the symmetric chain model of the evolutionary game of combination of stock markets. Based on the stable ratio of the rational and irrational investors and the asymptotically stable strategy of the model in the two cases, the paper uses the improved classic model of noise trading (DSSW) to calculate the irrational bubbles on the Shanghai stock market.
Findings
The paper shows that the more irrational investors are, the higher the irrational bubbles are.
Practical implications
The method exposed in the paper can be used to study the formation mechanism of the stock market bubble, to analyze the impact of investors' behaviours, to measure the size of irrational bubbles and to put forward some reasonable policy recommendations and preventive measures.
Originality/value
The paper succeeds in pointing out a new stock market's irrational bubble calculation model on the basis of evolutionary game chain structure, and thus measures the size of the Shanghai stock market bubble and makes some tentative research and discussion about the evolution law of the stock market's irrational bubble.
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Sifeng Liu, Zhigeng Fang, Chaoqing Yuan, Yaping Li and Ying Cao
The purpose of this paper is to propose a new system frame named ACPI for research and development (R&D) management of complex equipments according to the ideas of artificial…
Abstract
Purpose
The purpose of this paper is to propose a new system frame named ACPI for research and development (R&D) management of complex equipments according to the ideas of artificial societies, computational experiments, parallel execution and interactive optimization.
Design/methodology/approach
An artificial system which can effectively model, simulate and recur the main features and behaviors of a real R&D system of complex equipment is established at first. The structure and function of the system and its subsystems, and the relation of factors in the system are analyzed. Then one can perform computation experiment, modeling and simulation in the artificial system to obtain the optimal solutions. Finally, practice these solutions in a real system and at the same time perform the solutions in artificial system, forecasting and warning the possible new situations and problems in a realistic process, and provide controlling scheme.
Findings
The typical characteristics and solutions of the R&D system of complex equipment are analyzed. The sketch scheme of ACPI, the system frame of ACPI for R&D management of complex equipments are proposed, and the key technologies used in implementing ACPI of R&D system of complex equipment are studied.
Practical implications
The outcome of this paper can be used in computation experiments, management and optimization of R&D systems of complex equipment.
Originality/value
The sketch scheme of ACPI, the system frame of ACPI for R&D management of complex equipments are proposed first. The ACPI system can supply a high‐performance, open and interactive platform for the analog simulation and computation experiments of the R&D process management of complex equipment.
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Chaoqing Yuan, Benhai Guo and Hongqi Liu
As the world's largest developing country, China is relying on innovation to transform the pattern of economic growth; more and more attention has been paid to the construction of…
Abstract
Purpose
As the world's largest developing country, China is relying on innovation to transform the pattern of economic growth; more and more attention has been paid to the construction of China's regional innovation system (RIS). This paper aims to establish a provincial evaluation index system for RIS construction level and that of construction condition and evaluate the innovation system construction level and construction condition of China's provinces by using grey fixed weight clustering.
Design/methodology/approach
This paper makes a comprehensive assessment of RIS by using grey fixed weight clustering.
Findings
The results show that the construction level of RIS is clearly associated with construction condition of RIS. In accordance with the results of the assessment, China's 31 provinces are classified into four typical types. Some relevant key measures to promote the RIS are suggested.
Originality/value
This paper establishes a new frame to evaluate RIS.
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Benhai Guo, Rongrong Zhang and Chaoqing Yuan
This paper attempts to study the impact of changing incentive strategies on enterprises' energy saving effort level and to construct an effective principal‐agent mechanism to…
Abstract
Purpose
This paper attempts to study the impact of changing incentive strategies on enterprises' energy saving effort level and to construct an effective principal‐agent mechanism to achieve Pareto improvement of energy‐saving control.
Design/methodology/approach
Starting from the benefit relations between government and enterprises as well as their game strategies in energy conservation management, the impact of changing incentive strategies on enterprises' energy saving effort level and the asymmetric information situation of the players are studied taking into consideration the angle of strategies evolving in local government. Also, an effective principal‐agent mechanism to achieve Pareto improvement of energy‐saving control is constructed.
Findings
The results are convincing: interests of both the principal and agent had consistency under the principal‐agent mechanism, and the principal‐agent model was a mechanism with rich efficiency that could substantially arouse the enthusiasm of enterprises in energy saving. The comprehensive supervision of local governments over enterprises could effectually eliminate ill effects on energy‐saving management caused by information asymmetry under certain circumstances.
Practical implications
It is good for locating the balance of interest of game players by building a government energy saving mechanism based on principal‐agent theory. Through solving a game stable strategy, it is beneficial to seize a key point of regulation and control policies.
Originality/value
The paper succeeds in analyzing decision behaviours of government and enterprises through the basic idea of cooperative game theory so as to make actions of enterprises at all levels agree to government determined solving of energy issues.
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Qunfeng Wang, Zhigeng Fang, Yuqiang Guo, Chaoqing Yuan, Hongqi Liu and Ruiting Xu
The purpose of this paper is to realize scientific reasoning and prediction in economic catastrophe, which occurs in the short‐term and leads to invalidation of most classical…
Abstract
Purpose
The purpose of this paper is to realize scientific reasoning and prediction in economic catastrophe, which occurs in the short‐term and leads to invalidation of most classical prediction models through lacking basic sample data.
Design/methodology/approach
Based on functional theory, grey number algebra theory, Bayesian network theory and interval grey number theory, the authors established GFAM (1,1), which is grey function analysis model (1,1), to excavate and utilize the existing data sufficiently.
Findings
This paper proved least squares parameters theorem and prediction theorem and the process of GFAM (1,1). A case was established and demonstrated the utility and good prediction of this model.
Originality/value
This paper established GFAM (1,1), which overcomes the hysteretic defect of classical prediction model and provides a preferable solution in system prediction in economic catastrophe.