Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)

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Python-based Population Forecasting with Standard Deviation Analysis

Authors
Jiewen Zheng1, *
1NingboHuaMao International School, Ningbo, China
*Corresponding author. Email: Jacob.zheng@nbhis.com
Corresponding Author
Jiewen Zheng
Available Online 14 February 2024.
DOI
10.2991/978-94-6463-370-2_67How to use a DOI?
Keywords
Standard deviation; Population; Accuracy
Abstract

Changes in the world's population are a constant problem, such as the aging crescent, declining fertility and so on. Having an accurate forecast can chart a better and more useful plan for future development. The accuracy of the python prediction is obtained by computing the standard deviation of the python prediction and the raw data. The code runs within an extremely basic set of read, judge, and compute rules. This data set has been obtained from more than 10, 000 data sets of populations between 1950 and 2021 in different age conditions and countries. Each individual age segment gets a different shift during this period, especially for segments with large historical events, so it will be a challenge to see if Python can or cannot produce accurate predictions. In the experiments, python was used to predict the future population and the standard deviation was obtained by comparing the predicted results with the source data.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
Series
Advances in Intelligent Systems Research
Publication Date
14 February 2024
ISBN
978-94-6463-370-2
ISSN
1951-6851
DOI
10.2991/978-94-6463-370-2_67How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jiewen Zheng
PY  - 2024
DA  - 2024/02/14
TI  - Python-based Population Forecasting with Standard Deviation Analysis
BT  - Proceedings of the 2023 International Conference on Data Science, Advanced Algorithm and Intelligent Computing (DAI 2023)
PB  - Atlantis Press
SP  - 656
EP  - 665
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-370-2_67
DO  - 10.2991/978-94-6463-370-2_67
ID  - Zheng2024
ER  -