City Fire Forecasts and Analysis Based on Nonlinear Auto-Regressive Time-Series Model

Sheng Peng Liu; Ye Zhang

doi:10.4028/www.scientific.net/AMM.241-244.1550

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 241-244City Fire Forecasts and Analysis Based on...

City Fire Forecasts and Analysis Based on Nonlinear Auto-Regressive Time-Series Model

Abstract:

The forecasting to future developments of the city fire time series is a challenging task that has been addressed by many researchers due to the importance. In this paper, a Nonlinear Auto-Regressive (NAR) prediction model is applied to forecast the city fire data based on support vector regression. The performances of the NAR prediction model in city fire forecasting are compared with the BP neural network method. The experimental results show that the proposed model performs best.

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Periodical:

Applied Mechanics and Materials (Volumes 241-244)

Pages:

1550-1555

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.241-244.1550

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Online since:

December 2012

Authors:

Sheng Peng Liu, Ye Zhang

Keywords:

Nonlinear Auto-Regressive, Time-Series Model

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