title: A Monte Carlo simulation based two-stage adaptive resonance theory mapping approach for offshore oil spill vulnerability index classification.
abstract: In this paper, a Monte Carlo simulation based two-stage adaptive resonance theory mapping (MC-TSAM) model was developed to classify a given site into distinguished zones representing different levels of offshore Oil Spill Vulnerability Index (OSVI). It consisted of an adaptive resonance theory (ART) module, an ART Mapping module, and a centroid determination module. Monte Carlo simulation was integrated with the TSAM approach to address uncertainties that widely exist in site conditions. The applicability of the proposed model was validated by classifying a large coastal area, which was surrounded by potential oil spill sources, based on 12 features. Statistical analysis of the results indicated that the classification process was affected by multiple features instead of one single feature. The classification results also provided the least or desired number of zones which can sufficiently represent the levels of offshore OSVI in an area under uncertainty and complexity, saving time and budget in spill monitoring and response.
authors.affiliation: Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, Canada.
authors.forename: Pu
authors.initials: P
authors.lastname: Li
authors.affiliation: Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, Canada. Electronic address: bchen@mun.ca.
authors.forename: Bing
authors.initials: B
authors.lastname: Chen
authors.affiliation: Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, Canada.
authors.forename: Zelin
authors.initials: Z
authors.lastname: Li
authors.affiliation: Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, Canada.
authors.forename: Xiao
authors.initials: X
authors.lastname: Zheng
authors.affiliation: Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, Canada.
authors.forename: Hongjing
authors.initials: H
authors.lastname: Wu
authors.affiliation: Northern Region Persistent Organic Pollution Control (NRPOP) Laboratory, Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL, Canada.
authors.forename: Liang
authors.initials: L
authors.lastname: Jing
authors.affiliation: Wealth from Oceans National Research Flagship, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australian Resources Research Centre, Kensington, WA, Australia.
authors.forename: Kenneth
authors.initials: K
authors.lastname: Lee
mesh_terms: D003198:Computer Simulation; D062305:Geographic Mapping; D008962:Models, Theoretical; D009010:Monte Carlo Method; D059392:Petroleum Pollution / Q000032:analysis* / Q000517:prevention & control* / Q000706:statistics & numerical data; D018570:Risk Assessment / Q000379:methods*; D035501:Uncertainty
keywords: Adaptive resonance theory; Classification; Monte Carlo simulation; Offshore oil spill; Oil spill vulnerability index; Uncertainty