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A new method, Bayesian Programming (BP), developed by Harrison [Harrison KW. Multi-stage decision-making under uncertainty and stochasticity: Bayesian Programming. Adv Water Resour, submitted for publication] is tested on a case study involving optimal adaptive management of a river basin. The case study considers anew the process of permitting pulp mills on the Athabasca River in Alberta, Canada. The problem has characteristics common to many environmental management problems. There is uncertainty in the water quality response to pollutant loadings that will not be completely resolved with monitoring and the resolution of this uncertainty is impeded by the stochastic behavior of the water quality system. A two-stage adaptive management process is optimized with BP. Based on monitoring data collected after implementation of the first-stage decision, the uncertainties are updated prior to the second decision stage using Bayesian analysis. The worth of this two-stage adaptive management approach to this problem and the worth of monitoring are evaluated. Conclusions are drawn on the general practicality of BP for adaptive management. Potential strategies are outlined for extending the BP approach to secure further benefits of adaptive management. 相似文献
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《Marine Policy》2015
The sustainable science-based management of natural resources requires knowledge exchange between scientists and environmental decision-makers; however, evidence suggests that information flow is inhibited by a range of barriers. To date, our understanding of the range and importance of factors limiting knowledge exchange between scientists and decision-makers is based primarily on the perceptions of decision-makers, while the perceptions of scientists have been largely overlooked. This study addresses this knowledge gap by quantitatively assessing the perceptions of scientists, represented by a sample of 78 Australian marine scientists, regarding (i) the role and importance of engaging with environmental decision-makers on a personal level, (ii) the role and importance of engaging with environmental decision-makers at the institutional level, (iii) current barriers to engaging with environmental decision-makers and (iv) options for overcoming barriers to engaging with environmental decision-makers. Survey results suggest that Australian marine scientists feel that they have an obligation to engage decision-makers in their science, and that engaging with and communicating to environmental decision-makers is important on a personal level. This study also identifies a range of barriers that impede engagement activities, including inadequate measures of science impact that do not account for engagement activities, a lack of organisational support for engagement activities, insufficient time to conduct engagement activities in addition to other responsibilities and a lack of funding to support engagement activities. To overcome these barriers, participants identified the need for institutional innovation by research institutions, research funders and decision-making agencies alike to promote a culture whereby knowledge exchange activities are legitimised as core business for research scientists, and recognised and rewarded appropriately. Although difficulties exist in implementing such institutional innovations, doing so will improve two-way knowledge exchange among scientists and decision-makers and improve the likely success of environmental management. 相似文献
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地质图件及其附属资源（如描述文本）作为地质知识的重要存储媒介,蕴含着大量的地学知识及专家经验知识及隐式知识。快速精准地对多模态地质数据进行知识规范化定义、形式化表达、语义化关联和精准化推理是目前地学知识抽取及挖掘的前沿。当前,海量的地学数据中图件及附属描述信息知识分布零散,图件中的信息无法有效地与描述信息进行关联并提供知识服务。本文以多模态地质数据为数据源,建立了多源数据驱动下的地质图知识表达模型,通过地质基础知识、规则知识及决策知识来表达图件中蕴含的显隐式地质知识,从语义、空间、属性三个维度表示地质对象间的关系;并基于领域知识针对地质图件及描述信息开展了地质实体及关系的精准抽取及存储研究,最后以江西省于都县银坑幅G50E011007图幅150000矿产地质调查矢量数据为例进行了验证与分析,实验结果验证了本文所提出的知识表达模型及知识抽取方法, 能够较好地解决地质知识建模中图文关联弱、知识挖掘不充分等问题。 相似文献