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A Computational Method Of Forecasting Based On Fuzzy Time Series

机译:一种基于模糊时间序列的预测计算方法

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In this paper, a computational method of forecasting based on fuzzy time series have been developed to provide improved forecasting results to cope up the situation containing higher uncertainty due to large fluctuations in consecutive year's values in the time series data and having no visualization of trend or periodicity. The proposed model is of order three and uses a time variant difference parameter on current state to forecast the next state. The developed model has been tested on the historical student enrollments, University of Alabama to have comparison with the existing methods and has been implemented for forecasting of a crop production system of lahi crop, containing higher uncertainty. The suitability of the developed model has been examined in comparison with the other models to show its superiority.
机译:本文中,开发了一种基于模糊时间序列的预测计算方法,以提供改进的预测结果,以应对由于时间序列数据中连续年份的值出现较大波动而导致不确定性更高的情况,并且无法直观显示趋势或周期性。所提出的模型是三阶的,并且使用当前状态的时变差参数来预测下一个状态。所开发的模型已经在阿拉巴马大学的历史生招生中进行了测试,以与现有方法进行比较,并已用于预测拉希作物的作物生产系统,其中包含更高的不确定性。与其他模型相比,已开发模型的适用性进行了检验,以显示其优越性。

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