On analysing urban mobility data for smart cities - 2
The taxi industry in Singapore is one of the most important and integral part of Singapore’s transport landscape. When it comes to taking a taxi, Singaporeans prioritise the efficiency and the time saved when hailing a taxi. Therefore, it is crucial to understand the demand and supply of the taxis i...
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Nanyang Technological University
2022
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sg-ntu-dr.10356-1565622022-04-20T01:58:40Z On analysing urban mobility data for smart cities - 2 Ng, Sheryl Wenwei Cheng Long School of Computer Science and Engineering c.long@ntu.edu.sg Engineering::Computer science and engineering The taxi industry in Singapore is one of the most important and integral part of Singapore’s transport landscape. When it comes to taking a taxi, Singaporeans prioritise the efficiency and the time saved when hailing a taxi. Therefore, it is crucial to understand the demand and supply of the taxis in Singapore and this can be inferred from real-time taxi availability. This project aims to analyse the availability of taxis in Singapore and design a prediction model using different machine learning models. Bachelor of Engineering (Computer Engineering) 2022-04-20T01:58:40Z 2022-04-20T01:58:40Z 2022 Final Year Project (FYP) Ng, S. W. (2022). On analysing urban mobility data for smart cities - 2. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156562 https://hdl.handle.net/10356/156562 en SCSE21-0397 application/pdf Nanyang Technological University |
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Nanyang Technological University |
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NTU Library |
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Asia |
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Singapore Singapore |
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English |
| topic |
Engineering::Computer science and engineering |
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Engineering::Computer science and engineering Ng, Sheryl Wenwei On analysing urban mobility data for smart cities - 2 |
| description |
The taxi industry in Singapore is one of the most important and integral part of Singapore’s transport landscape. When it comes to taking a taxi, Singaporeans prioritise the efficiency and the time saved when hailing a taxi. Therefore, it is crucial to understand the demand and supply of the taxis in Singapore and this can be inferred from real-time taxi availability. This project aims to analyse the availability of taxis in Singapore and design a prediction model using different machine learning models. |
| author2 |
Cheng Long |
| author_facet |
Cheng Long Ng, Sheryl Wenwei |
| format |
Final Year Project |
| author |
Ng, Sheryl Wenwei |
| author_sort |
Ng, Sheryl Wenwei |
| title |
On analysing urban mobility data for smart cities - 2 |
| title_short |
On analysing urban mobility data for smart cities - 2 |
| title_full |
On analysing urban mobility data for smart cities - 2 |
| title_fullStr |
On analysing urban mobility data for smart cities - 2 |
| title_full_unstemmed |
On analysing urban mobility data for smart cities - 2 |
| title_sort |
on analysing urban mobility data for smart cities - 2 |
| publisher |
Nanyang Technological University |
| publishDate |
2022 |
| url |
https://hdl.handle.net/10356/156562 |
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1731235768911790080 |