The Journal of Grey System ›› 2024, Vol. 36 ›› Issue (3): 51-62.

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Exploring Death Population Prediction and Cemetery Planning in Chongqing amid an Aging Population: A Grey Forecast Model Based on Interval Grey Number 

  

  1. 1. Research Center for Economy of Upper Reaches of the Yangtze River Chongqing Technology and Business University, Chongqing 400067, China.  2. Chongqing Finance and Economics College, Chongqing 402160, China.  3. Chongqing Technology and Business University School of Management Science and Engineering, Chongqing 400067, China
  • Online:2024-06-21 Published:2024-06-20

Abstract: China’s population is steadily aging, contributing to the increase in the number of deceased people and the growing disparity between supply and demand for cemeteries. To provide theoretical support and data reference for cemetery planning, this study considers Chongqing, a city with a high rate of aging population, as an example to apply the interval grey number model to model and predict the size of the death population in Chongqing. The following conclusions are drawn: (1) The accuracy of the interval grey number prediction model in simulating the size of the death population in Chongqing exceeds 98%, indicating that the model employed in the study is suitable for medium- to long-term prediction; (2) The prediction results show that the annual death scale of registered population in Chongqing will range between 220 and 330 thousand from 2022 to 2030, with a fluctuating upward trend; (3) According to the size of the death population predicted, the cemetery market in Chongqing will experience a shortage of supply within 10 years. Therefore, in order to ensure a balance between the supply and demand of cemeteries in Chongqing, the government should actively promote the concept of green funerals and reduce the demand for cemeteries. Alternatively, it is also necessary to accelerate the planning and construction of cemeteries to avoid the predicament of people wanting to be buried without a tomb.  

Key words: Population aging, Prediction of death population size, Interval grey number prediction model, Suggestions for cemetery