  With the improvements of Los Angeles in many aspects, people in mounting
numbers tend to live or travel to the city. The primary objective of this paper
is to apply a set of methods for the time series analysis of traffic accidents
in Los Angeles in the past few years. The number of traffic accidents,
collected from 2010 to 2019 monthly reveals that the traffic accident happens
seasonally and increasing with fluctuation. This paper utilizes the ensemble
methods to combine several different methods to model the data from various
perspectives, which can lead to better forecasting accuracy. The IMA(1, 1),
ETS(A, N, A), and two models with Fourier items are failed in independence
assumption checking. However, the Online Gradient Descent (OGD) model generated
by the ensemble method shows the perfect fit in the data modeling, which is the
state-of-the-art model among our candidate models. Therefore, it can be easier
to accurately forecast future traffic accidents based on previous data through
our model, which can help designers to make better plans.
