Large-scale Pavement Crack Evaluation and Prediction using a Novel Spatial Machine Learning Approach
This study introduces a geocomplexity-enhanced machine learning (GML) model that integrates spatial methodologies to uncover influencing factors of crack severity obtained from human inspection and laser scanning. These two aspects, representing existing surface crack condition, are then integrated...
| Main Author: | |
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| Format: | Thesis |
| Published: |
Curtin University
2025
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| Online Access: | http://hdl.handle.net/20.500.11937/97702 |
| _version_ | 1848766307459137536 |
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| author | Chen, Chunjiang |
| author_facet | Chen, Chunjiang |
| author_sort | Chen, Chunjiang |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | This study introduces a geocomplexity-enhanced machine learning (GML) model that integrates spatial methodologies to uncover influencing factors of crack severity obtained from human inspection and laser scanning. These two aspects, representing existing surface crack condition, are then integrated with a risk of deterioration to develop a comprehensive crack evaluation framework. |
| first_indexed | 2025-11-14T11:49:04Z |
| format | Thesis |
| id | curtin-20.500.11937-97702 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T11:49:04Z |
| publishDate | 2025 |
| publisher | Curtin University |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-977022025-05-09T00:33:04Z Large-scale Pavement Crack Evaluation and Prediction using a Novel Spatial Machine Learning Approach Chen, Chunjiang This study introduces a geocomplexity-enhanced machine learning (GML) model that integrates spatial methodologies to uncover influencing factors of crack severity obtained from human inspection and laser scanning. These two aspects, representing existing surface crack condition, are then integrated with a risk of deterioration to develop a comprehensive crack evaluation framework. 2025 Thesis http://hdl.handle.net/20.500.11937/97702 Curtin University restricted |
| spellingShingle | Chen, Chunjiang Large-scale Pavement Crack Evaluation and Prediction using a Novel Spatial Machine Learning Approach |
| title | Large-scale Pavement Crack Evaluation and Prediction using a Novel Spatial Machine Learning Approach |
| title_full | Large-scale Pavement Crack Evaluation and Prediction using a Novel Spatial Machine Learning Approach |
| title_fullStr | Large-scale Pavement Crack Evaluation and Prediction using a Novel Spatial Machine Learning Approach |
| title_full_unstemmed | Large-scale Pavement Crack Evaluation and Prediction using a Novel Spatial Machine Learning Approach |
| title_short | Large-scale Pavement Crack Evaluation and Prediction using a Novel Spatial Machine Learning Approach |
| title_sort | large-scale pavement crack evaluation and prediction using a novel spatial machine learning approach |
| url | http://hdl.handle.net/20.500.11937/97702 |