Excellence in Research and Innovation for Humanity
%0 Journal Article
%A Tahseen A. Jilani and  S. M. Aqil Burney and  Cemal Ardil
%D 2008 
%J  International Journal of Computer, Electrical, Automation, Control and Information Engineering
%B World Academy of Science, Engineering and Technology
%I International Science Index 18, 2008
%T Multivariate High Order Fuzzy Time Series Forecasting for Car Road Accidents
%U http://waset.org/publications/15658
%V 18
%X In this paper, we have presented a new multivariate
fuzzy time series forecasting method. This method assumes mfactors
with one main factor of interest. History of past three years is
used for making new forecasts. This new method is applied in
forecasting total number of car accidents in Belgium using four
secondary factors. We also make comparison of our proposed
method with existing methods of fuzzy time series forecasting.
Experimentally, it is shown that our proposed method perform better
than existing fuzzy time series forecasting methods. Practically,
actuaries are interested in analysis of the patterns of causalities in
road accidents. Thus using fuzzy time series, actuaries can define
fuzzy premium and fuzzy underwriting of car insurance and life
insurance for car insurance. National Institute of Statistics, Belgium
provides region of risk classification for each road. Thus using this
risk classification, we can predict premium rate and underwriting of
insurance policy holders.
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