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- Publisher Website: 10.1061/(ASCE)0887-3801(2010)24:1(81)
- Scopus: eid_2-s2.0-73349121965
- WOS: WOS:000273037200010
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Article: Entropic risk analysis by a high level decision support system for construction SMEs
Title | Entropic risk analysis by a high level decision support system for construction SMEs |
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Authors | |
Keywords | Risk Construction industry Decision support systems Entropy Artificial intelligence |
Issue Date | 2010 |
Citation | Journal of Computing in Civil Engineering, 2010, v. 24, n. 1, p. 81-94 How to Cite? |
Abstract | The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects. © 2010 ASCE. |
Persistent Identifier | http://hdl.handle.net/10722/265463 |
ISSN | 2023 Impact Factor: 4.7 2023 SCImago Journal Rankings: 1.137 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Tang, L. C.M. | - |
dc.contributor.author | Leung, A. Y.T. | - |
dc.contributor.author | Wong, C. W.Y. | - |
dc.date.accessioned | 2018-12-03T01:20:44Z | - |
dc.date.available | 2018-12-03T01:20:44Z | - |
dc.date.issued | 2010 | - |
dc.identifier.citation | Journal of Computing in Civil Engineering, 2010, v. 24, n. 1, p. 81-94 | - |
dc.identifier.issn | 0887-3801 | - |
dc.identifier.uri | http://hdl.handle.net/10722/265463 | - |
dc.description.abstract | The method of entropy has been useful in evaluating inconsistency on human judgments. This paper illustrates an entropy-based decision support system called e-FDSS to the solution of multicriterion risk and decision analysis in projects of construction small and medium enterprises (SMEs). It is optimized and solved by fuzzy logic, entropy, and genetic algorithms. A case study demonstrated the use of entropy in e-FDSS on analyzing multiple risk criteria in the predevelopment stage of SME projects. Survey data studying the degree of impact of selected project risk criteria on different projects were input into the system in order to evaluate the preidentified project risks in an impartial environment. Without taking into account the amount of uncertainty embedded in the evaluation process; the results showed that all decision vectors are indeed full of bias and the deviations of decisions are finally quantified providing a more objective decision and risk assessment profile to the stakeholders of projects in order to search and screen the most profitable projects. © 2010 ASCE. | - |
dc.language | eng | - |
dc.relation.ispartof | Journal of Computing in Civil Engineering | - |
dc.subject | Risk | - |
dc.subject | Construction industry | - |
dc.subject | Decision support systems | - |
dc.subject | Entropy | - |
dc.subject | Artificial intelligence | - |
dc.title | Entropic risk analysis by a high level decision support system for construction SMEs | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1061/(ASCE)0887-3801(2010)24:1(81) | - |
dc.identifier.scopus | eid_2-s2.0-73349121965 | - |
dc.identifier.volume | 24 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 81 | - |
dc.identifier.epage | 94 | - |
dc.identifier.isi | WOS:000273037200010 | - |
dc.identifier.issnl | 0887-3801 | - |