An intelligent decision support system for management of petroleum-contaminated sites

Luo, Geng; Chen, Zhi; Chan, Christine W.; Huang, Guohe

doi:10.1016/s0957-4174(00)00063-4

Cited by 41 publications

(16 citation statements)

References 11 publications

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“…Some applications of decision support systems in process industries are described as follows. Geng et al (2001) presented a knowledge-based decision support system that aids users select petroleum contaminant remediation techniques based on user-specified information. Szladow and Mills (1996) described a DSS that presents the application work-flows used for training new operators in five heavy industries including iron and steel, cement, mining and metallurgy, oil and gas, and pulp and paper.…”

Section: Decision Support Systemmentioning

confidence: 99%

“…Knowledge acquisition (KA) is the process of elucidating, analyzing, transforming, classifying, organizing and integrating knowledge and representing that knowledge in a form that can be used in a computer system (Druzdzel & Flynn, 1999) (Geng et al, 2001). The objective of knowledge acquisition in this project is to obtain specific domain knowledge on how to filter and analyze CO 2 data.…”

Section: Knowledge Acquisitionmentioning

confidence: 99%

See 1 more Smart Citation

A Web-Based Data Management and Analysis System for CO2 Capture Process

Wu¹,

Chan²

2010

Decision Support Systems

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Section: Decision Support Systemmentioning

confidence: 99%

Section: Knowledge Acquisitionmentioning

confidence: 99%

A Web-Based Data Management and Analysis System for CO2 Capture Process

Wu¹,

Chan²

2010

Decision Support Systems

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“…Two cases were examined using the developed ES, with the derived outputs being compared with those from the source literature [17,21]). The details are provided as follows.…”

Section: System Validationmentioning

confidence: 99%

Development of an Expert System for the Remediation of Petroleum-Contaminated Sites

Chen

Huang

Chan

et al. 2003

Environmental Modeling & Assessment

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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.

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“…[1][2][3] taking into account the outstanding problems of contaminated site remediation technology screening exists, the paper carried out a screening method and its application based Tops is contaminated site remediation technologies.…”

Section: Introductionmentioning

confidence: 99%

Applied Research of Tops is Technology in Contaminated Soil Remediation

Lü¹,

Yang²,

Luo³

et al. 2015

Proceedings of the 2015 International Conference on Materials, Environmental and Biological Engineering

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Abstract. Multi-objective decision making method can make the evaluation process with intuitive and transparent, easily accepted by the people; rules of its evaluation process and realistic simulation calculation it will help to reduce the decision-making errors; multi-objective decision may also apply to group decision making, integrated consider one or more groups of decision makers multiple views and choose the best balanced solution. Thus managers remediation technology screening methods often used to repair various decision Screening.

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An intelligent decision support system for management of petroleum-contaminated sites

Cited by 41 publications

References 11 publications

A Web-Based Data Management and Analysis System for CO2 Capture Process

A Web-Based Data Management and Analysis System for CO2 Capture Process

Development of an Expert System for the Remediation of Petroleum-Contaminated Sites

Applied Research of Tops is Technology in Contaminated Soil Remediation

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