高阶直觉模糊时间序列预测模型

TP393.08; 提出一种高阶直觉模糊时间序列预测模型.模型首先应用模糊聚类算法实现论域的非等分划分;然后,针对直觉模糊时间序列的数据特性,提出一种更具客观性的直觉模糊集隶属度和非隶属度函数的确定方法;最后,利用直觉模糊多维取式推理建立高阶模型的预测规则,进行预测.在Alabama大学入学人数和北京市日均气温2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提高了预测精度,证明了模型的有效性和优越性....

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Published in通信学报 Vol. 37; no. 5; pp. 115 - 124
Main Authors 王亚男, 雷英杰, 雷阳, 范晓诗
Format Journal Article
LanguageChinese
Published 空军工程大学防空反导学院,陕西西安,710051%武警工程大学电子技术系密码与信息安全武警部队重点实验室,陕西西安,710086 2016
Subjects
intuitionistic fuzzy time series
high order
forecasting model
直觉模糊时间序列
直觉模糊推理
预测模型
intuitionistic fuzzy inference
高阶
Online AccessGet full text
ISSN1000-436X
DOI10.11959/j.issn.1000-436x.2016099

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Abstract TP393.08; 提出一种高阶直觉模糊时间序列预测模型.模型首先应用模糊聚类算法实现论域的非等分划分;然后,针对直觉模糊时间序列的数据特性,提出一种更具客观性的直觉模糊集隶属度和非隶属度函数的确定方法;最后,利用直觉模糊多维取式推理建立高阶模型的预测规则,进行预测.在Alabama大学入学人数和北京市日均气温2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提高了预测精度,证明了模型的有效性和优越性.
AbstractList TP393.08; 提出一种高阶直觉模糊时间序列预测模型.模型首先应用模糊聚类算法实现论域的非等分划分;然后,针对直觉模糊时间序列的数据特性,提出一种更具客观性的直觉模糊集隶属度和非隶属度函数的确定方法;最后,利用直觉模糊多维取式推理建立高阶模型的预测规则,进行预测.在Alabama大学入学人数和北京市日均气温2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提高了预测精度,证明了模型的有效性和优越性.
Author 雷英杰
王亚男
雷阳
范晓诗
AuthorAffiliation 空军工程大学防空反导学院,陕西西安,710051%武警工程大学电子技术系密码与信息安全武警部队重点实验室,陕西西安,710086
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Author_FL FAN Xiao-shi
LEI Yang
WANG Ya-nan
LEI Ying-jie
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Keywords intuitionistic fuzzy time series
high order
forecasting model
直觉模糊时间序列
直觉模糊推理
预测模型
intuitionistic fuzzy inference
高阶
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Publisher 空军工程大学防空反导学院,陕西西安,710051%武警工程大学电子技术系密码与信息安全武警部队重点实验室,陕西西安,710086
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Title 高阶直觉模糊时间序列预测模型
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