Applicability of SARIMA Model in Tokyo Population Migration Forecast

Shimizu, Shuto; Shin, Sanggyu

doi:10.1109/hsi52170.2021.9538690

Cited by 3 publications

(2 citation statements)

References 8 publications

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“…To improve the accuracy, factors such as the COVID-19 crisis were added. The results reflected that the model could be sufficiently used for such short-tomedium-term time-series data [63]. Similarly, three classes of model were employed by Fantazzini et al for out-of-sample forecasting of interregional migration in Russia; these include short-term forecasting using ARIMA and Google-augmented ARIMA models, as well as multivariate models for long-term forecasting.…”

Section: Time-series Modelsmentioning

confidence: 87%

Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction

Huang

Yang

et al. 2023

Sustainability

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As a fundamental, holistic, and strategic issue facing human society, human migration is a key factor affecting the development of countries and cities, given the constantly changing population numbers. The fuzziness of the spatiotemporal attributes of human migration limits the pool of open-source data for human migration prediction, leading to a relative lag in human migration prediction algorithm research. This study expands the definition of human migration research, reviews the progress of research into human migration prediction, and classifies and compares human migration algorithms based on open-source data. It also explores the critical uncertainty factors restricting the development of human migration prediction. Based on the analysis, there is no “best” migration prediction model, and data are key to forecasting human migration. Social media’s popularity and its increase in data have enabled the application of artificial intelligence in population migration prediction, which has attracted the attention of researchers and government administrators. Future research will aim to incorporate uncertainty into the predictive analysis framework, and explore the characteristics of population migration behaviors and their interactions. The integration of machine-learning and traditional data-driven models will provide a breakthrough for this purpose.

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Section: Time-series Modelsmentioning

confidence: 87%

Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction

Huang

Yang

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…internal migration, long-term, [38]; international migration, long-term, [39]; international migration, long-term, [40] ; international migration, long-term, [41]; international migration, short-term, [42]. internal migration, short-term, [43]; international migration, short-term, [44]; international migration, long-term, [45]; international migration, long-term, [46]; international migration, long-term, [47]; international migration, long and shortterm, [48]; international migration, longterm, [49]; internal migration, short-term, [50]; internal migration, short and longterm, [51].…”

Section: Research Progressmentioning

confidence: 99%

Transcending Time and Space: A Survey Methods, Uncertainty, and Development in Human Migration Prediction

Pu¹,

Huang²,

Yang³

et al. 2023

Preprint

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As a fundamental, overall, and strategic issue facing human society, human migration is a key factor affecting the development of countries and cities given constantly changing population numbers. The fuzziness of the spatiotemporal attributes of human migration limits the pool of open-source data for human migration prediction, leading to a relative lag in human migration prediction algorithm research. This study expands the definition of human migration research, reviews the progress of research into human migration prediction, and classifies and compares human migration algorithms based on open-source data. It also explores the critical uncertainty factors restricting the development of human migration prediction. Given the effect of human migration prediction, in combination with artificial intelligence and big data technology, the paper concludes with specific suggestions and countermeasures aimed at enhancing human migration prediction research results to serve economic and social development and national strategy.

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Efficient Time Series of Smoothing and Auto-regressive Forecasting Models for Predicting Police Officer Fatalities in the USA

Nagappan,

Jayabalan,

Alanezi

et al. 2024

Lecture Notes on Data Engineering and Communications Technologies

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Applicability of SARIMA Model in Tokyo Population Migration Forecast

Cited by 3 publications

References 8 publications

Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction

Transcending Time and Space: Survey Methods, Uncertainty, and Development in Human Migration Prediction

Transcending Time and Space: A Survey Methods, Uncertainty, and Development in Human Migration Prediction

Efficient Time Series of Smoothing and Auto-regressive Forecasting Models for Predicting Police Officer Fatalities in the USA

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