Application of game theory on parameter optimization of the novel two-stage Nash nonlinear grey Bernoulli model

Hsin, Pei-Han; Chen, Chun-I

doi:10.1016/j.cnsns.2015.03.006

Cited by 27 publications

(10 citation statements)

References 16 publications

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“…Shaikh et al [27] use the Levenberge Marquardt (LM) optimization principle to estimate the model parameters of the NGBM (1,1), and then carried out empirical comparison with regression models, traditional GM (1,1) and grey Verhulst models, the comparison indicates that NGBM (1,1) exhibits most favorable predicating accuracy. Hsin et al [28] built two-stage NGBM (1,1) model by iterative calculation of the two parameters (p and n) of the NGBM (1,1) model, which was used to predict the GDP of Taiwan. The model improves the forecasting precision of the model.…”

Section: The Development Of Grey Theory Modelmentioning

confidence: 99%

Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model

Pei

2019

Sustainability

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The new energy vehicles (NEVs) industry has been regarded as the primary industry involving in the transformation of the China automobile industry and environmental pollution control. Based on the quarterly fluctuation characteristics of NEVs’ sales volume in China, this research puts forwards a data grouping approach-based nonlinear grey Bernoulli model (DGA-based NGBM (1,1)). The main ideas of this work are to effectively predict quarterly fluctuation of NEVs industry by introducing a data grouping approach into the NGBM (1,1) model, and then use the particle swarm optimization (PSO) algorithm to optimize the parameters of the model so as to increase forecasting precision. By empirical comparison between the DGA-based NGBM (1,1) and existing data grouping approach-based GM (1,1) model (DGA-based GM (1,1)), DGA-based NGBM (1,1) can effectively reduce the prediction error resulting from quarterly fluctuation of sales volume of the NEVs, and prediction performance are proven to be favorable. The results of out-of-sample forecasting using the model proposed show that the sales volume of NEVs in China will increase by 57% in 2019–2020 with a quarterly fluctuation. In 2020, the sales volume of NEVs will exceeds the target of 2 million in the “13th Five-Year Strategic Development Plan”. Therefore, China needs to pay more attention to infrastructure construction and after-sales service for NEVs.

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Section: The Development Of Grey Theory Modelmentioning

confidence: 99%

Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model

Pei

2019

Sustainability

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“…Since the grey prediction model was proposed, it has been widely concerned by scholars. The existing studies mainly focus on the theoretical development from the aspects of background value optimization [3,4], parameter optimization [5][6][7], model expansion [8][9][10], and the application of natural gas [11,12], electric power [13][14][15][16], environment [17][18][19][20], economy [21,22], and transportation [23,24].…”

Section: Introductionmentioning

confidence: 99%

Fractional‐Order Accumulative Linear Time‐Varying Parameters Discrete Grey Forecasting Model

Gao

Zhan

Liu

2019

Mathematical Problems in Engineering

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Traditional discrete grey forecasting model can effectively predict the development trend of the stabilizing system. However, when the system has disturbance information, the prediction result will have larger error, and there will appear significant downward trend in the stability of the model. In the presence of disturbance information, this paper presents a fractional-order linear time-varying parameters discrete grey forecasting model to deal with the system that contains both linear trend and nonlinear trend. The modeling process of the model and calculation method are given. The perturbation bounds of the new model are analyzed by using the least-squares method of perturbation theory. And it is compared with that of the first-order linear time-varying parameters discrete grey forecasting model. Finally, two real cases are given to verify the effectiveness and practicality of the proposed method.

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“…For rational analysis, Pai et al (2007) used the grey relational grade of air pollutants from ambient air pollution and roadside air pollution monitoring stations to look at the relationship between air pollution and transportation. Moreover, grey model has been combined with many other methods to solve different problems: grey Bernoulli model (Pao et al , 2012), Nash non-linear grey model (Hsin and Chen, 2015), Fourier Grey model (Lin and Chiu, 2012), genetic algorithms grey theory (Wang and Hsu, 2008) and Grey-Markov model (Li et al , 2007).…”

Section: Introductionmentioning

confidence: 99%

A novel grey fixed weight cluster model based on interval grey numbers

Dang

2017

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Purpose Nowadays, evaluation objects are becoming more and more complicated. The interval grey numbers can be used to more accurately express the evaluation objects. However, the information distribution of interval grey numbers is not balanced. The purpose of this paper is to introduce the central-point triangular whitenization weight function to solve the clustering process of this kind of numbers. Design/methodology/approach A new expression of the central-point triangular whitenization weight function is presented in this paper, in terms of the grey cluster problem based on interval grey numbers. By establishing the integral mean value function on the set of interval grey numbers, the application range of grey clustering model is extended to the interval grey number category, and, in this way, the grey fixed weight cluster model based on interval grey numbers is obtained. Findings The model is verified by a case which reveals a high distinguishability, validity and practicability. Practical implications This model can be used in many fields, such as agriculture, economy, geology and medical science, and provides a feasible method for evaluation schemes in performance evaluation, scheme selection, risk evaluation and so on. Originality/value The central-point triangular whitenization weight function is introduced. The method reflects the thought “make full use of the information” in grey system theory and further enriches the system of grey clustering theory as well as expands the application scope of the grey clustering method.

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Application of game theory on parameter optimization of the novel two-stage Nash nonlinear grey Bernoulli model

Cited by 27 publications

References 16 publications

Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model

Forecasting Quarterly Sales Volume of the New Energy Vehicles Industry in China Using a Data Grouping Approach-Based Nonlinear Grey Bernoulli Model

Fractional‐Order Accumulative Linear Time‐Varying Parameters Discrete Grey Forecasting Model

A novel grey fixed weight cluster model based on interval grey numbers

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