Application of Kalman Filter Model Based on Hyperbolic Curve Model in the Deformation forecast

DOI

10.2991/iceep-17.2017.122How to use a DOI?

Keywords

hyperbolic curve model; Kalman filter; dynamic noise; settlement; forecast

Abstract

The hyperbolic curve model is erected, the least square method is used to obtain parameters of the hyperbolic curve model, parameters of the hyperbolic curve model are regarded as state vectors to contain dynamic noises to erect Kalman filter model based on the hyperbolic curve model, on the basis of Kalman filter model based on the hyperbolic curve model, settlement amounts of the building are forecasted. Because parameters of Kalman filter model change continuously in the process of Kalman filter, the ability that Kalman filter model suit the observation data is increased, and the fitting error of the model is lessened. An example of calculation shows that the forecast error is small, and the forecast effect is better to use Kalman filter model based on the hyperbolic curve model to forecast settlement amounts of the building .

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  - CONF
AU  - Fumin Lu
PY  - 2017/06
DA  - 2017/06
TI  - Application of Kalman Filter Model Based on Hyperbolic Curve Model in the Deformation forecast
BT  - Proceedings of the 2017 6th International Conference on Energy and Environmental Protection (ICEEP 2017)
PB  - Atlantis Press
SP  - 691
EP  - 694
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceep-17.2017.122
DO  - 10.2991/iceep-17.2017.122
ID  - Lu2017/06
ER  -