一种启发式变阶直觉模糊时间序列预测模型

王亚男; 雷英杰; 王毅; 郑寇全

doi:10.11999/JEIT160013

一种启发式变阶直觉模糊时间序列预测模型

doi: 10.11999/JEIT160013

1.
(空军工程大学防空反导学院西安 710051) ②(西安通信学院西安 710106)

基金项目:

国家自然科学青年基金项目(61402517)

计量
- 文章访问数: 1200
- HTML全文浏览量: 106
- PDF下载量: 415
- 被引次数: 0
出版历程
- 收稿日期: 2016-01-04
- 修回日期: 2016-05-26
- 刊出日期: 2016-11-19

A Heuristic Adaptive-order Intuitionistic Fuzzy Time Series Forecasting Model

1.
(Air and Missile Defense College, Air Force Engineering University, Xi&rsquo
2.
(Xi&rsquo

Funds:

The National Natural Science Foundation of China (61402517)

摘要

摘要: 论文针对已有高阶模糊时间序列模型在预测精度和预测范围上的限制，结合直觉模糊集理论，提出一种启发式变阶直觉模糊时间序列预测模型。模型首先应用直接模糊聚类算法对论域进行非等分划分；然后，针对直觉模糊时间序列的数据特性，改进现有直觉模糊集隶属度和非隶属度函数的建立方法；最后，采用阶数随序列实时变化的高阶预测规则进行预测，并将历史数据发展趋势的启发知识引入解模糊过程，使模型的预测范围得到扩展。在Alabama大学入学人数和北京市日均气温两组数据集上分别与典型方法进行对比实验，结果表明该模型有效克服了传统模型的缺点，拥有较高的预测精度，证明了模型的有效性和优越性。
- 直觉模糊集 /
- 时间序列预测 /
- 启发式 /
- 变阶
Abstract: Considering that the existing high-order models have limitations in forecast range and accuracy, a heuristic adaptive-order intuitionistic fuzzy time series forecasting model is built with the combination of the intuitionistic fuzzy sets theory. In this model, a direct fuzzy clustering algorithm is used to partition the universe of discourse into unequal intervals. The traditional method of ascertaining the membership and non-membership functions of intuitionistic fuzzy set are also modified to fit the intuitionistic fuzzy time series data. On these basis, variable high-order forecasting rules are established and the prior knowledge of tendency is used in defuzzification to extend the forecasting range. At last, contrast experiments on the enrollments of the University of Alabama and the daily average temperature of Beijing are carried out. The results show that the new model has a clear advantage of improving the forecast accuracy.
- Intuitionistic fuzzy set /
- Time series forecast /
- Heuristic /
- Adaptive order

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参考文献(33)

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