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A dynamic novel approach for bid/no-bid decision-making
The process of bid/no-bid decision-making is su bjected to uncertainty and influence of complex criteria. This paper proposed an application of the integration of rough sets (RS) and improved general regression neural network (GRNN) based on niche particle swarm optimization (NPSO) algorithm for ten...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025427/ https://www.ncbi.nlm.nih.gov/pubmed/27652162 http://dx.doi.org/10.1186/s40064-016-3230-1 |
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author | Shi, Huawang Yin, Hang Wei, Lianyu |
author_facet | Shi, Huawang Yin, Hang Wei, Lianyu |
author_sort | Shi, Huawang |
collection | PubMed |
description | The process of bid/no-bid decision-making is su bjected to uncertainty and influence of complex criteria. This paper proposed an application of the integration of rough sets (RS) and improved general regression neural network (GRNN) based on niche particle swarm optimization (NPSO) algorithm for tendering decision making. The decision table of RS and the attribution reduction was processed by MIBARK algorithm to simply the samples of GRNN. In order to improve the general regression neural network (GRNN) network performance, the niche particle swarm optimization (NPSO) was used to optimize the spread parameter σ of GRNN neural network, then a novel Bid/no-bid decision model was established based on RS and NPSO-GRNN neural network algorithm. The applicability of the proposed model was tested using real cases in Beijing. The results indicate that NPSO-GRNN algorithm has an advantage such as in prediction accuracy and generalization ability. The proposed decision support system approach is useful to help manager to make better Bid/no-bid decisions in uncertain construction markets, so they can take steps to prevent bid distress. |
format | Online Article Text |
id | pubmed-5025427 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-50254272016-09-20 A dynamic novel approach for bid/no-bid decision-making Shi, Huawang Yin, Hang Wei, Lianyu Springerplus Research The process of bid/no-bid decision-making is su bjected to uncertainty and influence of complex criteria. This paper proposed an application of the integration of rough sets (RS) and improved general regression neural network (GRNN) based on niche particle swarm optimization (NPSO) algorithm for tendering decision making. The decision table of RS and the attribution reduction was processed by MIBARK algorithm to simply the samples of GRNN. In order to improve the general regression neural network (GRNN) network performance, the niche particle swarm optimization (NPSO) was used to optimize the spread parameter σ of GRNN neural network, then a novel Bid/no-bid decision model was established based on RS and NPSO-GRNN neural network algorithm. The applicability of the proposed model was tested using real cases in Beijing. The results indicate that NPSO-GRNN algorithm has an advantage such as in prediction accuracy and generalization ability. The proposed decision support system approach is useful to help manager to make better Bid/no-bid decisions in uncertain construction markets, so they can take steps to prevent bid distress. Springer International Publishing 2016-09-15 /pmc/articles/PMC5025427/ /pubmed/27652162 http://dx.doi.org/10.1186/s40064-016-3230-1 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Shi, Huawang Yin, Hang Wei, Lianyu A dynamic novel approach for bid/no-bid decision-making |
title | A dynamic novel approach for bid/no-bid decision-making |
title_full | A dynamic novel approach for bid/no-bid decision-making |
title_fullStr | A dynamic novel approach for bid/no-bid decision-making |
title_full_unstemmed | A dynamic novel approach for bid/no-bid decision-making |
title_short | A dynamic novel approach for bid/no-bid decision-making |
title_sort | dynamic novel approach for bid/no-bid decision-making |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5025427/ https://www.ncbi.nlm.nih.gov/pubmed/27652162 http://dx.doi.org/10.1186/s40064-016-3230-1 |
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