Application of GM (1,1) and Seasonal Cross-Trend Model in the Forecast of Tourist Population in Sanya

Fan, Guo‐Feng; Jin, Xiang-Ru; Peng, Liling

doi:10.4018/ijaec.2019100103

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…Verhulst differential equation model is also a reliable method to describe population growth behavior (Brilhante et al , 2012). Linear regression model (Sulaiman et al , 2019), neural network model (Xiang and Liu, 2018) and the grey system model (Fan et al , 2019) are also commonly used methods. Various models have been developed based on their unique assumptions, characteristics and conditions (Tu and Chen, 2021).…”

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

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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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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

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“…According to the Bulletin of the Seventh National Population Census, the total number of aging people over 65 years old in China accounted for 13.50% in 2020, an increase of 4.63% compared with 2010, approaching the standard of aging coefficient of 14% in the stage of deep aging. At present, some scholars try to construct a new combination model [1][2][3] on the basis of the original models, such as population-developmentenvironment model [4], grey system model [5], neural network model [6][7], gene expression method [8], Bayesian hierarchical model [9], etc. Although the prediction accuracy has been improved, these models still ignore the reproduction process of the populations.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Population Aging Based on an Improved Markov Matrix

Zeng¹,

Duan²,

Jun³

2023

Atlantis Highlights in Computer Sciences

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Grasping the population aging from the perspective of long-term development has certain guiding significance of formulating national economic development plan and social strategic goals in China. Based on the Markov matrix and the population process reflected by Leslie matrix, an improved Markov matrix is constructed in this paper to predict the aging tendency of China's population. The prediction process takes full account of age-specific fertility rate, agespecific survival rate, male-to-female birth ratio and age-specific male-to-female ratio, which makes it have strong fault tolerance. It turns out that China's population will reach a peak of 1.42337 billion in 2027, and the proportion of the aging population will reach a maximum of 34.35% in 2060 and then begin to decline slightly, which can be traced to the second baby boom in Chinese history. But the proportion will remain above 25% until 2220. China's population aging is a long-term and non-cyclical process, and its deepening is mainly caused by the population structure not adapting to the population fertility pattern and life style under the background of the new era. Therefore, improving the population aging in China needs time to push forward the evolution of population structure. At the same time, China should develop a long-term sustainable aging economy to prepare for confronting the aging war and the "turning point".

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Application of GM (1,1) and Seasonal Cross-Trend Model in the Forecast of Tourist Population in Sanya

Cited by 2 publications

References 18 publications

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

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

Prediction of Population Aging Based on an Improved Markov Matrix

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