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Authors: Katsuhito Nakazawa ; Tetsuyoshi Shiota and Tsutomu Tanaka

Affiliation: Fujitsu Laboratories Ltd., Japan

ISBN: 978-989-758-199-1

Keyword(s): Causal Inference, Future Prediction, Time-series Data, Regional City, Social Issue.

Abstract: Regional cities in Japan have a lot of social issues. Various measures are being considered to solve these social issues, but it is difficult to ascertain and implement practical and effective measures to address them. In this study, we proposed a method for selecting indicators that have a causal relation to solve the social issues based on a causal inference. If there was a causal relation between two sets of time-series data, the slope of the approximation line of the time-shifted correlation coefficients at the base time returned a negative value. The causal inference was verified by using samples of time-series data and we constructed a network of the causal indicators based on the causal inference. In addition, we achieved future predictions via the vector autoregressive model using the network of causal indicators. The model was verified using the actual time-series data of the 87 regional cities. As a result, it was possible to simulate future predictions by introducing practi cal and effective measure that originated from the social issue. (More)

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Paper citation in several formats:
Nakazawa, K.; Shiota, T. and Tanaka, T. (2016). Future Prediction of Regional City based on Causal Inference using Time-series Data.In Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH, ISBN 978-989-758-199-1, pages 203-210. DOI: 10.5220/0005961902030210

@conference{simultech16,
author={Katsuhito Nakazawa. and Tetsuyoshi Shiota. and Tsutomu Tanaka.},
title={Future Prediction of Regional City based on Causal Inference using Time-series Data},
booktitle={Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,},
year={2016},
pages={203-210},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005961902030210},
isbn={978-989-758-199-1},
}

TY - CONF

JO - Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - Volume 1: SIMULTECH,
TI - Future Prediction of Regional City based on Causal Inference using Time-series Data
SN - 978-989-758-199-1
AU - Nakazawa, K.
AU - Shiota, T.
AU - Tanaka, T.
PY - 2016
SP - 203
EP - 210
DO - 10.5220/0005961902030210

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