Empirical study on the outliers of compressed nagural gas (CNG) refueling behaviors
- https://doi.org/10.2991/iccahe-16.2016.48How to use a DOI?
- CNG, Refueling behaviors, CNG filling station, Outlier, Python
To improve a secondary CNG filling station's refueling effectiveness and reduce its operation costs, the abnormal CNG refueling behaviors or outliers are empirically studied. Firstly, the central tendency and dispersion of volume and pressure change is empirically studied, and the simple regression model is adopted to test the positive correlation between the two variables. Secondly, the abnormal behaviors are detected by parametric methods and non-parametric methods of statistical approaches based on volume or pressure change. Finally, these outliers are found mainly from the repeated filling behaviors by Python language. Therefore, the way to improve the refueling effectiveness and reduce operation costs is to reduce repeated filling actions.
- © 2016, 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/).
Cite this article
TY - CONF AU - Yang Li AU - Dengchao Jin AU - Yulian Zhao AU - Zhenbo Bao AU - Weiyu Zhang AU - Yong Wei AU - Di Yang AU - Jian Shao PY - 2016/10 DA - 2016/10 TI - Empirical study on the outliers of compressed nagural gas (CNG) refueling behaviors BT - Proceedings of the 2016 5th International Conference on Civil, Architectural and Hydraulic Engineering (ICCAHE 2016) PB - Atlantis Press SP - 276 EP - 280 SN - 2352-5401 UR - https://doi.org/10.2991/iccahe-16.2016.48 DO - https://doi.org/10.2991/iccahe-16.2016.48 ID - Li2016/10 ER -