Group Decision Making Based Fuzzy Pattern Recognition Model for Lectotype Optimization of Offshore Platforms 1

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Setting conservation priorities in Fiji: Decision science versus additive scoring systems

There is a well-established scientific field – decision science – that can be used to rigorously set conservation priorities. Despite well-documented shortcomings, additive scoring approaches to conservation prioritization are still prevalent. This paper discusses the shortcomings and advantages of both approaches applied in Fiji to identify priorities for terrestrial protected areas. The two main shortcomings of using a scoring approach (discussed in Keppel (2014) [1]) that are resolved with decision science approaches (presented in Klein et al. (2014) [2]) in Fiji were (1) priorities did not achieve one of the most important stated conservation goals of representing ~40% of Fiji׳s major vegetation types and (2) the weighting of different selection criteria used was arbitrary. Both approaches considered expert knowledge and land–sea connections important to decision makers in Fiji, but only decision science can logically integrate both, in addition to other important considerations. Thus, decision makers are urged to use decision science and avoid additive scoring systems when prioritizing places for conservation. Fiji has the opportunity to be a global leader in using decision science to support integrated land–sea planning decisions.     

A fuzzy approach to the lectotype optimization of offshore platforms

Lectotype optimization of offshore platforms is of particular importance in the concept design process. Lectotype optimization involves multiple objectives with uncertainty and so is a problem of multiple attribute decision making. To date, there have been few published works on this topic in the context of offshore engineering. This paper develops a framework and methodology for evaluation of offshore platform alternatives, where a fuzzy optimum model is proposed to integrate the influence of each objective in the criteria set, and a new weight-assessing method is developed to mimic the decision maker’s experience and preference based on complementary pairwise comparisons. A case study shows that the new framework and methodology is scientific, reasonable and easy to use in practice.     

THESEUS decision support system for coastal risk management

While planning coastal risk management strategies, coastal managers need to assess risk across a range of spatial and temporal scales. GIS-based tools are one efficient way to support them in the decision making process through a scenarios analysis starting from social, economic and environmental information integrated into a common platform. However, this integration process requires a significant effort from a team of scientists in terms of a) identifying the appropriate scales and data resolution for analysing social, environmental and economic issues; b) selecting and linking an appropriate set of tools to build a coupled model; c) representing key emerging (and hence challenging) research issues, such as risk perception and social resilience in the model; d) developing multi-criteria analysis to integrate social, environmental, economic impacts; and e) accounting for the expectations of the stakeholders and therefore optimizing the opportunity for them to interact with the tool development and with the final tool itself.In this spirit, this paper presents an open-source Spatial Decision Support System developed within the THESEUS Project to help decision makers to scopeg optimal strategies to minimise coastal risks. The exploratory tool allows the users to perform an integrated coastal risk assessment, to analyse the effects of different combinations of engineering, social, economic and ecologically based mitigation options, across short (2020s), medium (2050s) and long-term (2080s) scenarios, taking into account physical and non-physical drivers, such as climate change, subsidence, population and economic growth.     

Large-scale offshore sand extraction: What could be the results of interaction between model and decision process?

The Netherlands is considering large-scale offshore sand extraction to meet the increasing demand for building sand, as the current supply of sand from land is insufficient. To develop a well-considered management policy to address this problem, knowledge about future morphological changes offshore caused by such an extraction is necessary. Such knowledge is not yet available. To support decisions about large-scale sand extraction, we developed a morphological model, which indicates possible effects of such extraction. However, because no field data is available, we cannot meet the requirement of decision makers to validate this model. Therefore, its results are controversial and difficult to use in decision-making. In this study, firstly we evaluate whether validation of the model would help the decision-making process about large-scale sand extraction? Secondly, we explore how we can use the invalidated model results in decision-making. And finally, we explore how to improve both the model and the use of the model without validation.Our opinion is that validation of the model will not solve the problem that decision makers deal with, and that although invalidated, decision makers can use the model results by using them as early warning signals. Interviews with the key players, to define the willingness to use the model results for decision-making, lead to useful recommendations to improve the model. These interviews were the first step of constructive technology assessment (CTA), which focuses on broadening the design and implementation process to stimulate the integration of societal criteria in the development of the model. Besides, these interviews appeared to have a positive influence on the willingness of the key players to use the model for decision-making. In general, we conclude that CTA, modulating the interaction between model and decision process, is a useful method for model makers that can help to make their models useful tools for decision-making.     

Fuzzy MCDM-based GIS model for subsea oil pipeline route optimization: An integrated approach

Proper pipeline route selection is an integral component of a typical oil exploration and transportation project. Improperly selected routes could have severe consequences including pipe failures, oil spillage, and environmental disasters. Consequently, technologies like geographic information systems (GIS) are increasingly being used to facilitate the oil pipeline route selection procedure—especially for onshore routing projects. Surprisingly, not much has been documented on the application of GIS to offshore pipeline routing. With recent discoveries on the merits of offshore oil exploration, it is necessary to extend the analytical capabilities of GIS to the unique offshore domain. However, concerns have been raised regarding the limitations of GIS in accurately prioritizing diverse selection criteria in typical multi-criteria decision-making (MCDM) problems like route selection. Consequently, this paper addresses the offshore/subsea pipeline routing constraint using a hybrid decision support system (DSS), which integrates a GIS and fuzzy logic-based approximate reasoning (AR) models for optimal performance. The resultant spatial decision support system (SDSS) was successfully applied to a case study in Malaysia. The AR algorithm calculated the significance level of the multiple criteria using various fuzzy linguistic variables and membership functions. The aggregated priority ranking from different pipeline routing experts showed that the overall influence of the environmental criteria (61.4%) significantly exceeded that of other equally important criteria in the study area. These rankings were inputted into the SDSS to simulate various probable routes. Final results accurately highlighted an optimal route, which places a premium on the protection of environmental features in the subsea study area—in alignment with the preferences of majority of the experts.     

多目标优选水下采油设施下放方法评价指标体系

水下采油设施下放是海上油气工程开发中的重要环节。经过长期发展,人们已研究出多种下放方法,但如何优选恰当的下放方法是尚待解决的问题。考虑海洋环境中可供数据源的复杂性、不确定性与不完整性,多目标、主客观要素并重是优选方法设计的重要准则。针对水下下放方法优选特点,建立对应评价指标体系。考虑评价指标体系多目标优选决策的特点,提出多目标非均一化灰色关联度模型;为更好地体现主客观要素并重并辩证表达决策者的主客观偏好,在非均一化处理中,运用回归原理与靶向偏差评价思想,提出变系数主客观权值修正模型。最后结合具体案例验证模型的可行性与有效性。结果表明,模型能够满足优选对象要求,对类似多目标主客观评价优选模型的建立具有一定借鉴意义。     

The interaction triangle as a tool for understanding stakeholder interactions in marine ecosystem based management

Expectations about ecosystem based management (EBM) differ due to diverging perspectives about what EBM should be and how it should work. While EBM by its nature requires trade-offs to be made between ecological, economic and social sustainability criteria, the diversity of cross-sectoral perspectives, values, stakes, and the specificity of each individual situation determine the outcome of these trade-offs. The authors strive to raise awareness of the importance of interaction between three stakeholder groups (decision makers, scientists, and other actors) and argue that choosing appropriate degrees of interaction between them in a transparent way can make EBM more effective in terms of the three effectiveness criteria salience, legitimacy, and credibility. This article therefore presents an interaction triangle in which three crucial dimensions of stakeholder interactions are discussed: (A) between decision makers and scientists, who engage in framing to foster salience of scientific input to decision making, (B) between decision makers and other actors, to shape participation processes to foster legitimacy of EBM processes, and (C) between scientists and other actors, who collaborate to foster credibility of knowledge production. Due to the complexity of EBM, there is not one optimal interaction approach; rather, finding the optimal degrees of interaction for each dimension depends on the context in which EBM is implemented, i.e. the EBM objectives, the EBM initiator’s willingness for transparency and interaction, and other context-specific factors, such as resources, trust, and state of knowledge.     

模糊层次分析法在浅剖数据质量评价中的应用

为解决浅剖数据质量评价指标不一、定量化不足的问题,本文基于层次分析法的原理,结合德尔菲法及模糊评价方法,建立了浅剖质量评价的模糊层次分析技术流程,构建了多层次的浅剖质量评价模型,确定了3个一级指标和14个二级指标,给出了各指标在质量评价中的定量权重,定出了4个质量评价等级。文章应用评价模型对深海及浅海两套浅剖数据集进行了评价,根据评价结果及最大隶属度原则,深海浅剖数据总体质量为中等,浅海浅剖数据总体质量为良好。结果显示,该模型可以有效地将专家主观经验以知识驱动的形式转成定量化评价指标,给出的评价结果客观、可量化,减少了数据质量评价过程中人为主观因素影响和片面性,可为数据进一步应用提供较为准确的应用等级建议。     

基于模糊网络耦合模型的舟山蓝色海湾整治项目综合社会效益评估研究

模糊网络耦合模型（Fuzzy-ANP）是一种兼顾数理性和系统性的社会效益评价工具,因其对不同评价指标相互影响的深度考量而被广泛运用于复杂社会工程项目的效益评价中。本文引入模糊网络耦合模型对舟山蓝色海湾整治行动项目的综合社会效益进行评估,通过构建基础模型、优化指标体系、综合系统测评,最终形成对项目的综合社会效益总评（83.53分）。评价结果不仅能对项目整体社会效益作出判断,亦有益于项目后期维护实施及同类项目效益测评参考。     

模糊模式识别用于找矿预测

本文提出两类模糊模式识别用于找矿预测的具体方法．用Ｆ－ＰＦＳ法和调节特征因素及其权重以获取最佳分类，聚类中心即作为标准模式．根据单因素判对率确立了因素逆距离权重的概念．在标准模式的模糊向量与已知单元模糊向量之间关系的基础上可以建二线性不等式方程组，从而可解不同因素的距离权重，并进而用贴近度对未知单元进行识别．以上方法应用于鄂东南地区的铜及多金属的找矿预测，结果表明方法有效。成果较好。     

Biogeographic assessments: A framework for information synthesis in marine spatial planning

This paper presents the Biogeographic Assessment Framework (BAF), a decision support process for marine spatial planning (MSP), developed through two decades of close collaborations between scientists and marine managers. Spatial planning is a considerable challenge for marine stewardship agencies because of the need to synthesize information on complex socio-ecological patterns across geographically broad spatial scales. This challenge is compounded by relatively short time-frames for implementation and limited financial and technological resources. To address this pragmatically, BAF provides a rapid, flexible and multi-disciplinary approach to integrate geospatial information into formats and visualization tools readily useable for spatial planning. Central to BAF is four sequential components: (1) Planning; (2) Data Evaluation; (3) Ecosystem Characterization; and (4) Management Applications. The framework has been applied to support the development of several marine spatial plans in the United States and Territories. This paper describes the structure of the BAF framework and the associated analytical techniques. Two management applications are provided to demonstrate the utility of BAF in supporting decision making in MSP.     

3-D underwater object recognition

In this paper, we propose an automatic supervised classification of objects lying on the sea floor or buried in sediment layers. This pattern recognition provides a way to distinguish natural and manufactured objects and then should be helpful to detect mine, pipe-line, or wreckage. Proposed methods combine different techniques: pattern information extraction, relevant parameter search, and supervised classifier. Parameters are automatically selected using a principal component analysis to reduce misclassification rate and to simplify classifier structure. Performances of different parameters (two-dimensional and three-dimensional) are compared and discussed from testing on synthetic and real data bases.     

Spatial policy and the behavior of fishermen

Fishery policy makers would often benefit from information on how a policy might change fishermen behavior before the policy is implemented. This paper contributes to the literature by comparing simulated behavioral response with actual response to a spatial policy using a discrete choice model of fishing location choice. The results point to the inherent problem of the simulation's inability to capture the fundamental change in the nature of the choice problem that occurs with the change in policy. Addressing this problem will be important as these models continue to be used to inform policy makers.     

基于模糊聚类的声呐图像多区域分割

图像分割是图像识别中的主要问题,同时它又是一个经典难题;声呐图像恶劣的品质使图像的分割变得更为困难。文章将模糊聚类应用于声呐图像的多区域分割,实验证明这种方法简便而有效。     

An integration of multi-criteria decision making techniques with a delay time model for determination of inspection intervals for marine machinery systems

For certain critical equipment items in marine machinery systems, the optimum maintenance strategy would be a scheduled on-condition operation. This involves inspection of the equipment items in order to monitor their performance degradation and, invariably, carry out repair or replacement tasks. The main challenge with this type of maintenance approach is the determination of the appropriate interval for performing the inspection task. This paper presents a methodology which integrates multi-criteria decision making (MCDM) tools with a delay time model for the determination of optimum inspection intervals for marine machinery systems. With this approach, multiple decision criteria are modelled with the delay time concept and aggregated with MCDM tools such that different criteria can be applied simultaneously in the ranking of different inspection interval alternatives. The applicability of the proposed methodology is demonstrated using the case study of a water cooling pump of the central cooling system of a marine diesel engine.     

Managing coastal area resources by stated choice experiments

In many coastal regions, oil spills can be considered as one of the most important and certainly the most noticeable forms of marine pollution. Efficient contingency management responding to oil spills on waters, which aims at minimizing pollution effects on coastal resources, turns out to be critically important. Such a decision making highly depends on the importance attributed to different coastal economic and ecological resources. Economic uses can, in principal, be addressed by standard measures such as value added. However, there is a missing of market in the real world for natural goods. Coastal resources such as waters and beach cannot be directly measured in money terms, which increases the risk of being neglected in a decision making process. This paper evaluates these natural goods of coastal environment in a hypothetical market by employing stated choice experiments. Oil spill management practice in German North Sea is used as an example. Results from a pilot survey show that during a combat process, beach and eider ducks are of key concerns for households. An environmental friendly combat option has to be a minor cost for households. Moreover, households with less children, higher monthly income and a membership of environmental organization are more likely to state that they are willing to pay for combat option to prevent coastal resources from an oil pollution. Despite that choice experiments require knowledge of designing questionnaire and statistical skills to deal with discrete choices and conducting a survey is time consumed, the results have important implications for oil spill contingency management. Overall, such a stated preference method can offer useful information for decision makers to consider coastal resources into a decision making process and can further contribute to finding a cost-effective oil preventive measure, also has a wide application potential in the field of Integrated Coastal Zone Management (ICZM).     

A tool for site prioritisation of marine protected areas under data poor conditions

A challenge of managing data poor fisheries lies in overcoming uncertainties associated with a lack of information on biological and socio-economic conditions. This paper focuses on site prioritisation for marine protected areas, a process that usually imposes moderate to heavy demands on data, time, local expertise, and funds. A fuzzy logic decision support tool for zoning marine areas that is suitable for use in data poor conditions is developed. This tool, the Protected Area Suitability Index (PASI), assesses the suitability of sites for protection based on fishers’ preferences for that site and the site’s conservation value. Only eight input attributes are required to run the PASI, which operates on a series of heuristic rules to estimate a site suitability score that ranges from 0 to 10, where 10 indicates that a site is highly suitable for being protected from fishing. Sensitivity analysis reveals that the PASI is relatively robust, and produces reliable results even as the system is degraded by the loss of data. Eighteen actively fished sites and 11 sites that are closed to fishing are assessed to evaluate how well the PASI is able to distinguish differences between sites. The estimated scores are significantly different (p<0.05), whereby non-fished sites are scored as being more suitable for protection than fished sites. The PASI can be used as a decision support tool to facilitate systematic marine spatial management under data poor conditions, especially in the task of identifying suitable sites for protection.     

Stakeholder objective preferences in Australian Commonwealth managed fisheries

Fisheries management is increasingly involving a wide range of stakeholders in the decision making process. However, in most fisheries, the set of management objectives are poorly defined, and the implicit importance placed on these objectives may vary considerably both between and within different stakeholder groups. This may lead to conflicts within management advisory groups where members from different stakeholder groups view potential management outcomes substantially differently, and inconsistencies in decision making when changes in stakeholder representation take place. In this paper, the institutional structure of fisheries management in Australia and the roles the different organisations play in shaping fisheries management plans are detailed. An explicit hierarchy of management objectives is developed in collaboration with key managers and policy makers. A large survey of stakeholders involved in Australian Commonwealth fisheries management was undertaken to determine stakeholder preferences relating to these objectives. The results highlight the differences in perspectives regarding the relative importance of the multiple objectives of fisheries management. While on average stakeholder preferences generally correspond with their expected preference set, the results also indicate that there is generally low coherence within stakeholder groups.     

Sea Grant in Latin America?: Adapting the US Sea Grant model of linked applied research,extension, and education to a Latin American Context—Is there a fit?

This paper explores the application of the US Sea Grant model of applied research, extension, and education to two case studies in Latin America: Coastal Ecuador and the Gulf of Fonseca. The analysis is based on a series of meetings and roundtables with in-country partners and leaders of the US Sea Grant program. We conclude that the Sea Grant model provides an institutional structure that Latin America lacks and the model's features would improve governance of marine and coastal resources through more effective linkages between coastal communities, universities, and policy/decision makers at local, national, and international levels.