Improvement and Evaluation of Estimation of Time Series Data of Daily Life

DOI

10.2991/ijndc.2017.5.4.5How to use a DOI?

Keywords

Estimation, Daily life data, Multiple regression analysis, Day type, Rainfall, Temperature.

Abstract

This paper improves the estimation of the amounts of sewage flow, which is one of daily life data, in order to manage them efficiently. The amounts of flow of a typical day are tried to be adjusted to those of a non-regular day. A typical (non-regular, respectively) day is a non-rainy day having good data and no (a few) outliers. The values for the adjustment are tried to be estimated by using the multiple regression analysis. It is shown that the estimation can be improved, and these values can be estimated by using the temperature of that day, the amount of the rain fall of the previous day, and the day type, which distinguishes a weekday, Saturday, Sunday, and a national holiday. The estimation is tried to be used in estimating the data of a regular day. It is experimentally shown that the estimation works well.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - JOUR
AU  - Teruhisa Hochin
AU  - Hiroki Nomiya
PY  - 2017
DA  - 2017/10/02
TI  - Improvement and Evaluation of Estimation of Time Series Data of Daily Life
JO  - International Journal of Networked and Distributed Computing
SP  - 233
EP  - 242
VL  - 5
IS  - 4
SN  - 2211-7946
UR  - https://doi.org/10.2991/ijndc.2017.5.4.5
DO  - 10.2991/ijndc.2017.5.4.5
ID  - Hochin2017
ER  -