Forecasting the development trend of new energy vehicles in China by an optimized fractional discrete grey power model

Liu, Lianyi; Liu, Sifeng; Wu, Lifeng; Zhu, Junsheng; Shang, Gang

doi:10.1016/j.jclepro.2022.133708

Cited by 45 publications

(17 citation statements)

References 32 publications

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“…Compared with previous studies, which mainly focuses on NEV sales and penetration, a typical study performed by Liu et al introduced an optimized fractional discrete grey power model with the predicted results of China’s NEV sales to be 8.84 million in 2025, which is more conservative than our study [ 48 ]. Liu et al used deep learning technology to forecast the NEVs indicating the NEV market will reach the 20% penetration goal in 2025, which is in accordance with our study while we provided a more specific figure instead of simply a percentage of market share [ 49 ].…”

Section: Resultsmentioning

confidence: 66%

A Sustainable Road Transport Decarbonisation: The Scenario Analysis of New Energy Vehicle in China

Chen

You

Liu³

et al. 2023

IJERPH

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Due to the prosperous development of the economy, the emissions of carbon dioxide (CO2) and other greenhouse gases (GHGs) have intensified and attracted attention worldwide. China has set the “dual-carbon” aim to pursue sustainable development in the transport sector. Thus, this study created a generalised Bass model to forecast new energy vehicle (NEV) ownership by introducing a new factor, charging piles, to reflect the infrastructure effects. Using the improved model with the hypothesis of annual mileage, an empirical analysis was conducted with the subject of NEVs in China by using the NEV-related panel data from 2010 to 2020, and the forecast result is outstanding with a goodness-of-fit of 99.7%. With the forecasts, carbon emission reduction was calculated with a bottom-up method. To further discuss the pathway to achieve carbon neutrality in the transport sector of China, a scenario analysis was conducted with ideal, enhanced, and radical constraints. The results show that if all factors remain “as is” until 2050, China will be far from carbon neutrality. Thus, this paper proposes relevant policy implications to assist the government to obtain effective methods to assess carbon reduction benefits and find viable pathways to a sustainable road transport system.

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Section: Resultsmentioning

confidence: 66%

A Sustainable Road Transport Decarbonisation: The Scenario Analysis of New Energy Vehicle in China

Chen

You

Liu³

et al. 2023

IJERPH

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“…For instance, the grey system model is used to tackle the issue of poor information and uncertainty. It can extract useful information from its own time series to build a model and has shown promising prediction performance for time series with limited data (Qian and Sui, 2021; Zhou et al ., 2022; Li et al , 2022b; Liu et al ., 2022).…”

Section: Introductionmentioning

confidence: 99%

A novel fractional-order discrete grey Gompertz model for analyzing the aging population in Jiangsu Province, China

Zhang

Liu

et al. 2023

Self Cite

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PurposeChina's population aging is gradually deepening and needs to be actively addressed. The purpose of this paper is to construct a novel model for analyzing the population aging.Design/methodology/approachTo analyze the aging status of a region, this study has considered three major indicators: total population, aged population and the proportion of the aged population. Additionally, the authors have developed a novel grey population prediction model that incorporates the fractional-order accumulation operator and Gompertz model (GM). By combining these techniques, the authors' model provides a comprehensive and accurate prediction of population aging trends in Jiangsu Province. This research methodology has the potential to contribute to the development of effective policy solutions to address the challenges posed by the population aging.FindingsThe fractional-order discrete grey GM is suitable for predicting the aging population and has good performance. The population aging of Jiangsu Province will continue to deepen in the next few years.Practical implicationsThe proposed model can be used to predict and analyze aging differences in Jiangsu Province. Based on the prediction and analysis results, identified some corresponding countermeasures are suggested to address the challenges of Jiangsu's future aging problem.Originality/valueThe fractional-order discrete grey GM is firstly proposed in this paper and this model is a novel grey population prediction model with good performance.

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“…Then, considering the power function type growth of observed data or time series factors, a time-varying discrete power model DTGPM was proposed by Liu et al . (2022a, b).Model parameter optimization (Mao et al ., 2015; Cheng and Shi, 2022). Research on this class of optimization models has focused on the optimization of model performance parameters (initial value, background value and cumulative order) (Wang et al ., 2018; Tong et al ., 2022).…”

Section: Introductionmentioning

confidence: 99%

“…(2022) established the MCMGM(1, N ) model and Liu et al . (2022a, b) proposed the WFNGBM(1,1, N ) model. The full consideration of model structure optimization is achieved in FDGM(1,1, k 2 , r ) and FDGM(1,1, √k, r ), and the models have both linear and nonlinear driving terms.…”

Section: Introductionmentioning

confidence: 99%

A novel grey prediction model with structure variability and real domain fractional order and its performance comparisons

Mao¹,

Gou²,

Zeng³

2023

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PurposeThis paper aims to overcome the problem that the single structure of the driving term of the grey prediction model is not adapted to the complexity and diversity of the actual modeling objects, which leads to poor modeling results.Design/methodology/approachFirstly, the nonlinear law between the raw data and time point is fully mined by expanding the nonlinear term and the range of order. Secondly, through the synchronous optimization of model structure and parameter, the dynamic adjustment of the model with the change of the modeled object is realized. Finally, the objective optimization of nonlinear driving term and cumulative order of the model is realized by particle swarm optimization PSO algorithm.FindingsThe model can achieve strong compatibility with multiple existing models through parameter transformation. The synchronous optimization of model structure and parameter has a significant improvement over the single optimization method. The new model has a wide range of applications and strong modeling capabilities.Originality/valueA novel grey prediction model with structure variability and optimizing parameter synchronization is proposed.HighlightsThe highlights of the paper are as follows:A new grey prediction model with a unified nonlinear structure is proposed.The new model can be fully compatible with multiple traditional grey models.The new model solves the defect of poor adaptability of the traditional grey models.The parameters of the new model are optimized by PSO algorithm.Cases verify that the new model outperforms other models significantly.

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Forecasting the development trend of new energy vehicles in China by an optimized fractional discrete grey power model

Cited by 45 publications

References 32 publications

A Sustainable Road Transport Decarbonisation: The Scenario Analysis of New Energy Vehicle in China

A Sustainable Road Transport Decarbonisation: The Scenario Analysis of New Energy Vehicle in China

A novel fractional-order discrete grey Gompertz model for analyzing the aging population in Jiangsu Province, China

A novel grey prediction model with structure variability and real domain fractional order and its performance comparisons

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