Qualitative phase space reconstruction analysis of supply-chain inventor time series
The economy systems are usually too complex to be analysed, but some advanced methods have been developed in order to do so, such as system dynamics modelling, multi-agent modelling, complex adaptive system modelling and qualitative modelling. In this paper, we considered a supply-chain (SC) syst...
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doaj-faeba01fdf854cdfa83858d0dba0391a2021-04-04T20:05:36ZengAcademy of Science of South AfricaSouth African Journal of Science1996-74892010-11-0110611/12Qualitative phase space reconstruction analysis of supply-chain inventor time seriesChenxi Shao0Lizhong Wang1Lipeng Xiao2Jinliang Wu3University of Science and Technology of ChinaUniversity of Science and Technology of ChinaUniversity of Science and Technology of ChinaUniversity of Science and Technology of ChinaThe economy systems are usually too complex to be analysed, but some advanced methods have been developed in order to do so, such as system dynamics modelling, multi-agent modelling, complex adaptive system modelling and qualitative modelling. In this paper, we considered a supply-chain (SC) system including several kinds of products. Using historic suppliers' demand data, we firstly applied the phase space analysis method and then used qualitative analysis to improve the complex system's performance. Quantitative methods can forecast the quantitative SC demands, but they cannot indicate the qualitative aspects of SC, so when we apply quantitative methods to a SC system we get only numerous data of demand. By contrast, qualitative methods can show the qualitative change and trend of the SC demand. We therefore used qualitative methods to improve the quantitative forecasting results. Comparing the quantitative only method and the combined method used in this paper, we found that the combined method is far more accurate. Not only is the inventory cost lower, but the forecasting accuracy is also better.http://192.168.0.118/index.php/sajs/article/view/9905data miningphase spacequalitative forecastingquantitative forecastingsupply chain management |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Chenxi Shao Lizhong Wang Lipeng Xiao Jinliang Wu |
spellingShingle |
Chenxi Shao Lizhong Wang Lipeng Xiao Jinliang Wu Qualitative phase space reconstruction analysis of supply-chain inventor time series South African Journal of Science data mining phase space qualitative forecasting quantitative forecasting supply chain management |
author_facet |
Chenxi Shao Lizhong Wang Lipeng Xiao Jinliang Wu |
author_sort |
Chenxi Shao |
title |
Qualitative phase space reconstruction analysis of supply-chain inventor time series |
title_short |
Qualitative phase space reconstruction analysis of supply-chain inventor time series |
title_full |
Qualitative phase space reconstruction analysis of supply-chain inventor time series |
title_fullStr |
Qualitative phase space reconstruction analysis of supply-chain inventor time series |
title_full_unstemmed |
Qualitative phase space reconstruction analysis of supply-chain inventor time series |
title_sort |
qualitative phase space reconstruction analysis of supply-chain inventor time series |
publisher |
Academy of Science of South Africa |
series |
South African Journal of Science |
issn |
1996-7489 |
publishDate |
2010-11-01 |
description |
The economy systems are usually too complex to be analysed, but some advanced methods have been developed in order to do so, such as system dynamics modelling, multi-agent modelling, complex adaptive system modelling and qualitative modelling. In this paper, we considered a supply-chain (SC) system including several kinds of products. Using historic suppliers' demand data, we firstly applied the phase space analysis method and then used qualitative analysis to improve the complex system's performance. Quantitative methods can forecast the quantitative SC demands, but they cannot indicate the qualitative aspects of SC, so when we apply quantitative methods to a SC system we get only numerous data of demand. By contrast, qualitative methods can show the qualitative change and trend of the SC demand. We therefore used qualitative methods to improve the quantitative forecasting results. Comparing the quantitative only method and the combined method used in this paper, we found that the combined method is far more accurate. Not only is the inventory cost lower, but the forecasting accuracy is also better. |
topic |
data mining phase space qualitative forecasting quantitative forecasting supply chain management |
url |
http://192.168.0.118/index.php/sajs/article/view/9905 |
work_keys_str_mv |
AT chenxishao qualitativephasespacereconstructionanalysisofsupplychaininventortimeseries AT lizhongwang qualitativephasespacereconstructionanalysisofsupplychaininventortimeseries AT lipengxiao qualitativephasespacereconstructionanalysisofsupplychaininventortimeseries AT jinliangwu qualitativephasespacereconstructionanalysisofsupplychaininventortimeseries |
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1721541626865647616 |