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Comparison of Fuzzy Percentage and Classic Model, Evaluate the Strength of Short-term Forecast in Severe Fluctuations
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Mehrdad Eslami   , Fatemeh Hassantabar Darzi * |
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Abstract: (2578 Views) |
Fuzzy time series prediction models have been expanding in recent decades. These models provide decent behavior for unambiguous and incomplete data that do not have a linear structure. This paper examines the fuzzy percentage change model and compared to Arima's model. The efficiency of the proposed model for forecasting OPEC crude oil was evaluated and it was shown that this model has a lower error rate for data with high volatility.
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| Keywords: Percent changes, time series, fuzzy, ARIMA model. |
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Full-Text [PDF 337 kb]
(1685 Downloads)
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Type of Study: Applicable |
Subject:
Special
Received: 2017/07/15 | Accepted: 2018/07/7 | Published: 2019/01/7
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