Please use this identifier to cite or link to this item:
http://hdl.handle.net/20.500.11861/6778| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Dr. KWOK Pak Ki, Alex | en_US |
| dc.contributor.author | Chau, D. W. H. | en_US |
| dc.contributor.author | Lau, Y. K. Henry | en_US |
| dc.date.accessioned | 2021-11-29T01:45:04Z | - |
| dc.date.available | 2021-11-29T01:45:04Z | - |
| dc.date.issued | 2014 | - |
| dc.identifier.citation | In Bramer, M. & Petridis, M. (eds.) (2014). Research and development in intelligent systems XXXI (pp. 339-344). | en_US |
| dc.identifier.uri | http://hdl.handle.net/20.500.11861/6778 | - |
| dc.description.abstract | With the increasing number of vehicles on roads, choosing a proper Road Junction Control (RJC) Method has become an important decision for reducing traffic congestion and cost. However, the public awareness of environmental sustainability and diverse voices from different stakeholders make such decision a knotty one. In this paper, an artificial intelligent decision-making framework using Hierarchical Half Fuzzy TOPSIS (HHF-TOPSIS) is proposed for RJC method selection. Compared with the existing qualitative comparison method suggested in the Design Manual for Roads and Bridges, this method can provide a more efficient and objective approach to reach the best compromise against all relevant objectives. | en_US |
| dc.language.iso | en | en_US |
| dc.title | A study on road junction control method selection using an artificial intelligent multi-criteria decision making framework | en_US |
| dc.type | Conference Paper | en_US |
| dc.relation.conference | International Conference on Innovative Techniques and Applications of Artificial Intelligence | en_US |
| item.fulltext | No Fulltext | - |
| Appears in Collections: | Publication | |
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