Time Measurement of People's Cultural Life Quality in China 's Provinces Based on Grey Prediction

In order to better counter the quality of people's cultural life in various regions of China, based on the scientific and effective principles of data, this paper collects 33 secondary indicators for evaluating the quality of people 's cultural life from 31 provinces in China from 2014 to 2022. Then, the box plot and mean interpolation method are used to deal with outliers and missing values, and then the heat map is used to evaluate and screen the index system. In order to more accurately reflect the quality of cultural life, this paper uses the entropy weight method to integrate the second-level indicators into a more comprehensive first-level indicator, and obtains the specific scores of 31 provinces in ' cultural participation', 'cultural industrialization', 'cultural creativity', 'cultural richness' and 'cultural resources 'from 2014 to 2022, so as to do basic work for subsequent prediction and comprehensive evaluation. Finally, in order to enhance the innovation of the model, this paper studies the quality of cultural life of Chinese people in each province by 2025 under the grey prediction model from the time dimension, taking into account the scientific and effective. This method is conducive to China 's full understanding of the differences and convergence of the quality of cultural life in various provinces, providing a scientific basis for the cultural construction of the world 's people, and promoting social progress and civilization development.

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Publication Details

Journal
Journal of Education Humanities and Social Sciences
Published
2024-08-15
DOI
https://doi.org/10.54097/7dhyrr87
Primary Topic
Diverse Aspects of Tourism Research
Type
article
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article

Time Measurement of People's Cultural Life Quality in China 's Provinces Based on Grey Prediction

Xiyu Zeng, Ruikang Liang, Liancai Shen, Yiwang Zhong
Journal of Education Humanities and Social Sciences
Diverse Aspects of Tourism Research
article

Time Measurement of People's Cultural Life Quality in China 's Provinces Based on Grey Prediction

Xiyu Zeng, Ruikang Liang, Liancai Shen, Yiwang Zhong
article en

Abstract

In order to better counter the quality of people's cultural life in various regions of China, based on the scientific and effective principles of data, this paper collects 33 secondary indicators for evaluating the quality of people 's cultural life from 31 provinces in China from 2014 to 2022. Then, the box plot and mean interpolation method are used to deal with outliers and missing values, and then the heat map is used to evaluate and screen the index system. In order to more accurately reflect the quality of cultural life, this paper uses the entropy weight method to integrate the second-level indicators into a more comprehensive first-level indicator, and obtains the specific scores of 31 provinces in ' cultural participation', 'cultural industrialization', 'cultural creativity', 'cultural richness' and 'cultural resources 'from 2014 to 2022, so as to do basic work for subsequent prediction and comprehensive evaluation. Finally, in order to enhance the innovation of the model, this paper studies the quality of cultural life of Chinese people in each province by 2025 under the grey prediction model from the time dimension, taking into account the scientific and effective. This method is conducive to China 's full understanding of the differences and convergence of the quality of cultural life in various provinces, providing a scientific basis for the cultural construction of the world 's people, and promoting social progress and civilization development.

Journal of Education Humanities and Social SciencesVol. 37
Guangdong University of Technology (CN), Shenzhen University (CN)
Decent work and economic growth
Openalex Percentile: Top 79%
Diverse Aspects of Tourism Research
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Time Measurement of People's Cultural Life Quality in China 's Provinces Based on Grey Prediction — Xiyu Zeng, Ruikang Liang, et al. · Journal of Education Humanities and Social Sciences (2024) | TGRS Research Map | TGRS