Inaccuracy Minimization by Partioning Fuzzy Data Sets - Validation of Analystical Methodology

Details Inaccuracy Minimization by Partioning Fuzzy Data Sets - Validation of Analystical Methodology Inaccuracy Minimization by Partioning Fuzzy Data Sets - Validation of Analystical Methodology

2010-05-24

arxiv.org/abs/1005.4272v1

Computer Science

Artificial Intelligence

IEEE Publication format, International Journal of Computer Science and Information Security, IJCSIS, Vol. 8 No. 1, April 2010,

Scientific paper

In the last two decades, a number of methods have been proposed for forecasting based on fuzzy time series. Most of the fuzzy time series methods are presented for forecasting of car road accidents. However, the forecasting accuracy rates of the existing methods are not good enough. In this paper, we compared our proposed new method of fuzzy time series forecasting with existing methods. Our method is based on means based partitioning of the historical data of car road accidents. The proposed method belongs to the kth order and time-variant methods. The proposed method can get the best forecasting accuracy rate for forecasting the car road accidents than the existing methods.

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