Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process

Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process

Uncertain statistics is a methodology for collecting and interpreting the expert’s experimental data by uncertainty theory. In order to estimate uncertainty distributions, an optimization model based on analytic hierarchy process (AHP) and interpolation method is proposed in this paper. In addition,...

Full description

Bibliographic Details
Main Author: Yongchao Hou
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2014/594025
id doaj-1ae4b541e31643f0878a7580cc1c753e
record_format Article
spelling doaj-1ae4b541e31643f0878a7580cc1c753e2020-11-24T23:00:41ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472014-01-01201410.1155/2014/594025594025Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy ProcessYongchao Hou0Department of Mathematical Sciences, Chaohu University, Anhui 238000, ChinaUncertain statistics is a methodology for collecting and interpreting the expert’s experimental data by uncertainty theory. In order to estimate uncertainty distributions, an optimization model based on analytic hierarchy process (AHP) and interpolation method is proposed in this paper. In addition, the principle of least squares method is presented to estimate uncertainty distributions with known functional form. Finally, the effectiveness of this method is illustrated by an example.http://dx.doi.org/10.1155/2014/594025
collection DOAJ
language English
format Article
sources DOAJ
author Yongchao Hou
spellingShingle Yongchao Hou
Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
Mathematical Problems in Engineering
author_facet Yongchao Hou
author_sort Yongchao Hou
title Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
title_short Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
title_full Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
title_fullStr Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
title_full_unstemmed Optimization Model for Uncertain Statistics Based on an Analytic Hierarchy Process
title_sort optimization model for uncertain statistics based on an analytic hierarchy process
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2014-01-01
description Uncertain statistics is a methodology for collecting and interpreting the expert’s experimental data by uncertainty theory. In order to estimate uncertainty distributions, an optimization model based on analytic hierarchy process (AHP) and interpolation method is proposed in this paper. In addition, the principle of least squares method is presented to estimate uncertainty distributions with known functional form. Finally, the effectiveness of this method is illustrated by an example.
url http://dx.doi.org/10.1155/2014/594025
work_keys_str_mv AT yongchaohou optimizationmodelforuncertainstatisticsbasedonananalytichierarchyprocess
_version_ 1725641514398253056

Similar Items