What is it about?
This paper utilized the components in time series such as secular trend, irregular fluctuation, cyclical and seasonal movements to extrapolate prediction using multiplicative model. The main objective of this research is to predict fire risk in short-range period based on the past data.
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Why is it important?
This study analyzed fire data in the city of Manila from 2011-2015 and predicted the possible occurrence of fire and its risk. A tally of 2823 fire incidents were included in this study and as recorded based on the cumulative frequency, Electrical failure is most cause of fire incident with an average of 315 cases per year.
Perspectives
The significance of understanding fire risk using Time series forecasting must be utilize and administer, which can be useful tool to serve as guide and help to mitigate fire incidents.
Francis Balahadia
Read the Original
This page is a summary of: Time series forecasting using multiplicative model: A predictive model for fire risk in the city of Manila, December 2017, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/scored.2017.8305410.
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