Development of an expert system for the remediation of petroleum-contaminated sites
文献类型：SCI/SSCI论文
| 作者 | Xia J. |
| 发表日期 | 2003 |
| 关键词 | petroleum waste soil groundwater remediation artificial intelligence expert system contamination environmental risk assessment underground-storage tanks |
| 英文摘要 | Groundwater and soil contamination caused by light nonaqueous phase liquids (LNAPLs) spills and leakage in petroleum industry is currently one of the major environmental concerns in North America. Numerous site remediation technologies, generally classified as ex situ and in situ remediation techniques, have been developed and implemented to clean up the contaminated sites in the last two decades. One of the problems associated with ex situ remediation is the cost of operation. In recent years, in situ techniques have acquired popularity. However, the selection process of the desired techniques needs a large amount of knowledge. Insufficient expertise in the process may result in unnecessary inflation of expenses. In this study, petroleum waste management experts and Artificial Intelligence ( AI) researchers worked together to develop an expert system ( ES) for the management of petroleum contaminated sites. Various AI techniques were used to construct a useful tool for site remediation decision-making. This paper presents the knowledge engineering processes of knowledge acquisition, conceptual design, and system implementation in the project. The expert system was applied to a real-world case study and the results show that the expert system can generate desired remediation alternatives to assist decision-makers. The application case study constitutes partial validation of the prototype expert system. |
| 出处 | Environmental Modeling & Assessment |
| 卷 | 8 |
| 期 | 4 |
| 页 | 323-334 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 1420-2026 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/24201]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Xia J.. Development of an expert system for the remediation of petroleum-contaminated sites. 2003. |
入库方式： OAI收割
来源：地理科学与资源研究所
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