926 resultados para Environmental Decision Suport System


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Cover title: Towards the development of a county employment projection system for the state of Illinois.

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With marine biodiversity conservation the primary goal for reserve planning initiatives, a site's conservation potential is typically evaluated on the basis of the biological and physical features it contains. By comparison, socio-economic information is seldom a formal consideration of the reserve system design problem and generally limited to an assessment of threats, vulnerability or compatibility with surrounding uses. This is perhaps surprising given broad recognition that the success of reserve establishment is highly dependent on widespread stakeholder and community support. Using information on the spatial distribution and intensity of commercial rock lobster catch in South Australia, we demonstrate the capacity of mathematical reserve selection procedures to integrate socio-economic and biophysical information for marine reserve system design. Analyses of trade-offs highlight the opportunities to design representative, efficient and practical marine reserve systems that minimise potential loss to commercial users. We found that the objective of minimising the areal extent of the reserve system was barely compromised by incorporating economic design constraints. With a small increase in area (< 3%) and boundary length (< 10%), the economic impact of marine reserves on the commercial rock lobster fishery was reduced by more than a third. We considered also how a reserve planner might prioritise conservation areas using information on a planning units selection frequency. We found that selection frequencies alone were not a reliable guide for the selection of marine reserve systems, but could be used with approaches such as summed irreplaceability to direct conservation effort for efficient marine reserve design.

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Whilst traditional optimisation techniques based on mathematical programming techniques are in common use, they suffer from their inability to explore the complexity of decision problems addressed using agricultural system models. In these models, the full decision space is usually very large while the solution space is characterized by many local optima. Methods to search such large decision spaces rely on effective sampling of the problem domain. Nevertheless, problem reduction based on insight into agronomic relations and farming practice is necessary to safeguard computational feasibility. Here, we present a global search approach based on an Evolutionary Algorithm (EA). We introduce a multi-objective evaluation technique within this EA framework, linking the optimisation procedure to the APSIM cropping systems model. The approach addresses the issue of system management when faced with a trade-off between economic and ecological consequences.

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There have been many models developed by scientists to assist decision-makers in making socio-economic and environmental decisions. It is now recognised that there is a shift in the dominant paradigm to making decisions with stakeholders, rather than making decisions for stakeholders. Our paper investigates two case studies where group model building has been undertaken for maintaining biodiversity in Australia. The first case study focuses on preservation and management of green spaces and biodiversity in metropolitan Melbourne under the umbrella of the Melbourne 2030 planning strategy. A geographical information system is used to collate a number of spatial datasets encompassing a range of cultural and natural assets data layers including: existing open spaces, waterways, threatened fauna and flora, ecological vegetation covers, registered cultural heritage sites, and existing land parcel zoning. Group model building is incorporated into the study through eliciting weightings and ratings of importance for each datasets from urban planners to formulate different urban green system scenarios. The second case study focuses on modelling ecoregions from spatial datasets for the state of Queensland. The modelling combines collaborative expert knowledge and a vast amount of environmental data to build biogeographical classifications of regions. An information elicitation process is used to capture expert knowledge of ecoregions as geographical descriptions, and to transform this into prior probability distributions that characterise regions in terms of environmental variables. This prior information is combined with measured data on the environmental variables within a Bayesian modelling technique to produce the final classified regions. We describe how linked views between descriptive information, mapping and statistical plots are used to decide upon representative regions that satisfy a number of criteria for biodiversity and conservation. This paper discusses the advantages and problems encountered when undertaking group model building. Future research will extend the group model building approach to include interested individuals and community groups.

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Expert systems, and artificial intelligence more generally, can provide a useful means for representing decision-making processes. By linking expert systems software to simulation software an effective means of including these decision-making processes in a simulation model can be achieved. This paper demonstrates how a commercial-off-the-shelf simulation package (Witness) can be linked to an expert systems package (XpertRule) through a Visual Basic interface. The methodology adopted could be used for models, and possibly software, other than those presented here.

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As levels of investment in advanced manufacturing systems increase, effective project management becomes ever more critical. This paper demonstrates how the model proposed by Mintzberg, Raisinghani and Theoret in 1976, which structures complicated strategic decision processes, can be applied to the design of new production systems for both descriptive and analytical research purposes. This paper sets a detailed case study concerning the design and development of an advanced manufacturing system within the Mintzberg decision model and so breaks down the decision sequence into constituent parts. It thus shows how a structured model can provide a framework for the researcher who wishes to study decision episodes in the design of manufacturing facilities in greater depth.

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When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

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This research compared decision making processes in six Chinese state-owned enterprises during the period 1985 to 1988. The research objectives were: a) To examine changes in the managerial behaviour over a period of 1985 to 1988 with a focus on decision-making; b) Through this examination, to throw light on the means by which government policies on economic reform were implemented at the enterprise level; c) To illustrate problems encountered in the decentralization programme which was a major part of China's economic reform. The research was conducted by means of intensive interviews with more than eighty managers and a survey of documents relating to specific decisions. A total of sixty cases of decision-making were selected from five decision topics: purchasing of inputs, pricing of outputs, recruitment of labour, organizational change and innovation, which occurred in 1985 (or before) and in 1988/89. Data from the interviews were used to investigate environmental conditions, relations between the enterprise and its higher authority, interactions between management and the party system, the role of information, and effectiveness of regulations and government policies on enterprise management. The analysis of the data indicates that the decision processes in the different enterprises have some similarities in regard to actor involvement, the flow of decision activities, interactions with the authorities, information usage and the effect of regulations. Comparison of the same or similar decision contents over time indicates that the achievement of decentralization varied according to the topic of decision. Managerial authority was delegated to enterprises when the authorities relaxed their control over resource allocation. When acquisition of necessary resources is dependent upon the planning system or the decision matter is sensitive, because it involves change to the institutional framework (e.g. the Party), then a high degree of centralization was retained, resulting in a marginal change in managerial behaviour. The economic reform failed to increase decision efficiency and effectiveness of decision-making. The prevailing institutional frameworks were regarded as negative to the change. The research argues that the decision process is likely to be more contingent on the decision content than the organization. Three types of decision process have been conceptualized, each of them related to a certain type of decision content. This argument gives attention to the perspectives of institution and power in a way which facilitates an elaboration of organizational analysis. The problems encountered in the reform of China's industrial enterprises are identified and discussed. General recommendations for policies of further reform are offered, based on the analysis of decision process and managerial behaviour.

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Manufacturing systems that are heavily dependent upon direct workers have an inherent complexity that the system designer is often ill-equipped to understand. This complexity is due to the interactions that cause variations in performance of the workers. Variation in human performance can be explained by many factors, however one important factor that is not currently considered in any detail during the design stage is the physical working environment. This paper presents the findings of ongoing research investigating human performance within manufacturing systems. It sets out to identify the form of the relationships that exist between changes in physical working environmental variables and operator performance. These relationships can provide managers with a decision basis when designing and managing manufacturing systems and their environments.

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Dynamically adaptive systems (DASs) are intended to monitor the execution environment and then dynamically adapt their behavior in response to changing environmental conditions. The uncertainty of the execution environment is a major motivation for dynamic adaptation; it is impossible to know at development time all of the possible combinations of environmental conditions that will be encountered. To date, the work performed in requirements engineering for a DAS includes requirements monitoring and reasoning about the correctness of adaptations, where the DAS requirements are assumed to exist. This paper introduces a goal-based modeling approach to develop the requirements for a DAS, while explicitly factoring uncertainty into the process and resulting requirements. We introduce a variation of threat modeling to identify sources of uncertainty and demonstrate how the RELAX specification language can be used to specify more flexible requirements within a goal model to handle the uncertainty. © 2009 Springer Berlin Heidelberg.