| contributor author | Stephen G. Ritchie | |
| contributor author | Che‐I Yeh | |
| contributor author | Joe P. Mahoney | |
| contributor author | Newton C. Jackson | |
| date accessioned | 2017-05-08T21:02:15Z | |
| date available | 2017-05-08T21:02:15Z | |
| date copyright | March 1987 | |
| date issued | 1987 | |
| identifier other | %28asce%290733-947x%281987%29113%3A2%28155%29.pdf | |
| identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/36303 | |
| description abstract | Pavement surface condition data play a pivotal role in the analysis and design of pavement rehabilitation strategies. In project design, this information is usually used by a limited number of pavement engineering specialists who apply experience and judgment to formulate design and investment decisions. The nature of this process resists computerization using conventional computer tools. The development of a knowledge‐based expert system that is based on programming concepts from the field of artificial intelligence is described. The system is called SCEPTRE, and assists highway engineers in planning cost‐effective flexible pavement rehabilitation strategies at the project level. The use of an expert‐systems approach permits SCEPTRE to make its specialized body of knowledge accessible to a much broader range of potential engineering users. | |
| publisher | American Society of Civil Engineers | |
| title | Surface Condition Expert System for Pavement Rehabilitation Planning | |
| type | Journal Paper | |
| journal volume | 113 | |
| journal issue | 2 | |
| journal title | Journal of Transportation Engineering, Part A: Systems | |
| identifier doi | 10.1061/(ASCE)0733-947X(1987)113:2(155) | |
| tree | Journal of Transportation Engineering, Part A: Systems:;1987:;Volume ( 113 ):;issue: 002 | |
| contenttype | Fulltext | |
