926 resultados para Environmental Decision Suport System


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A decision support system SonaRes destined to guide and help the ultrasound operators is proposed and compared with the existing ones. The system is based on rules and images and can be used as a second opinion in the process of ultrasound examination.

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The paper presents a multicriteria decision support system, called MultiDecision-2, which consists of two independent parts - MKA-2 subsystem and MKO-2 subsystem. MultiDecision-2 software system supports the decision makers (DMs) in the solving process of different problems of multicriteria analysis and linear (continues and integer) problems of multicriteria optimization. The two subsystems MKA-2 and MKO-2 of of MultiDecision-2 are briefly described in the paper in the terms of the class of the problems being solved, the system structure, the operation with the interface modules for input data entry and the information about DM’s local preferences, as well as the operation with the interface modules for visualization of the current and final solutions.

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Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.

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* This paper is partially supported by the National Science Fund of Bulgarian Ministry of Education and Science under contract № I–1401\2004 "Interactive Algorithms and Software Systems Supporting Multicriteria Decision Making."

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This paper describes the basic tools for a real-time decision support system of a semiotic type on the example of the prototype for management and monitoring of a nuclear power block implemented on the basis of the tool complex G2+GDA using cognitive graphics and parallel processing. This work was supported by RFBR (project 02-07-90042).

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Vendor-managed inventory (VMI) is a widely used collaborative inventory management policy in which manufacturers manages the inventory of retailers and takes responsibility for making decisions related to the timing and extent of inventory replenishment. VMI partnerships help organisations to reduce demand variability, inventory holding and distribution costs. This study provides empirical evidence that significant economic benefits can be achieved with the use of a genetic algorithm (GA)-based decision support system (DSS) in a VMI supply chain. A two-stage serial supply chain in which retailers and their supplier are operating VMI in an uncertain demand environment is studied. Performance was measured in terms of cost, profit, stockouts and service levels. The results generated from GA-based model were compared to traditional alternatives. The study found that the GA-based approach outperformed traditional methods and its use can be economically justified in small- and medium-sized enterprises (SMEs).

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This paper investigates neural network-based probabilistic decision support system to assess drivers' knowledge for the objective of developing a renewal policy of driving licences. The probabilistic model correlates drivers' demographic data to their results in a simulated written driving exam (SWDE). The probabilistic decision support system classifies drivers' into two groups of passing and failing a SWDE. Knowledge assessment of drivers within a probabilistic framework allows quantifying and incorporating uncertainty information into the decision-making system. The results obtained in a Jordanian case study indicate that the performance of the probabilistic decision support systems is more reliable than conventional deterministic decision support systems. Implications of the proposed probabilistic decision support systems on the renewing of the driving licences decision and the possibility of including extra assessment methods are discussed.

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This paper presents a development of decision support systems for solving scheduling problems. It consists of two parts — the first describing the production processes which can be handled by the system and the second describing how the system works.

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Increased pressure to control costs and increased competition has prompted health care managers to look for tools to effectively operate their institutions. This research sought a framework for the development of a Simulation-Based Decision Support System (SB-DSS) to evaluate operating policies. A prototype of this SB-DSS was developed. It incorporates a simulation model that uses real or simulated data. ER decisions have been categorized and, for each one, an implementation plan has been devised. Several issues of integrating heterogeneous tools have been addressed. The prototype revealed that simulation can truly be used in this environment in a timely fashion because the simulation model has been complemented with a series of decision-making routines. These routines use a hierarchical approach to organize the various scenarios under which the model may run and to partially reconfigure the ARENA model at run time. Hence, the SB-DSS tailors its responses to each node in the hierarchy.

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This paper deals with a very important issue in any knowledge engineering discipline: the accurate representation and modelling of real life data and its processing by human experts. The work is applied to the GRiST Mental Health Risk Screening Tool for assessing risks associated with mental-health problems. The complexity of risk data and the wide variations in clinicians' expert opinions make it difficult to elicit representations of uncertainty that are an accurate and meaningful consensus. It requires integrating each expert's estimation of a continuous distribution of uncertainty across a range of values. This paper describes an algorithm that generates a consensual distribution at the same time as measuring the consistency of inputs. Hence it provides a measure of the confidence in the particular data item's risk contribution at the input stage and can help give an indication of the quality of subsequent risk predictions. © 2010 IEEE.

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This report is the product of a first-year research project in the University Transportation Centers Program. This project was carried out by an interdisciplinary research team at The University of Iowa's Public Policy Center. The project developed a computerized system to support decisions on locating facilities that serve rural areas while minimizing transportation costs. The system integrates transportation databases with algorithms that specify efficient locations and allocate demand efficiently to service regions; the results of these algorithms are used interactively by decision makers. The authors developed documentation for the system so that others could apply it to estimate the transportation and route requirements of alternative locations and identify locations that meet certain criteria with the least cost. The system was developed and tested on two transportation-related problems in Iowa, and this report uses these applications to illustrate how the system can be used.

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BACKGROUND: Errors in the decision-making process are probably the main threat to patient safety in the prehospital setting. The reason can be the change of focus in prehospital care from the traditional "scoop and run" practice to a more complex assessment and this new focus imposes real demands on clinical judgment. The use of Clinical Guidelines (CG) is a common strategy for cognitively supporting the prehospital providers. However, there are studies that suggest that the compliance with CG in some cases is low in the prehospital setting. One possible way to increase compliance with guidelines could be to introduce guidelines in a Computerized Decision Support System (CDSS). There is limited evidence relating to the effect of CDSS in a prehospital setting. The present study aimed to evaluate the effect of CDSS on compliance with the basic assessment process described in the prehospital CG and the effect of On Scene Time (OST). METHODS: In this time-series study, data from prehospital medical records were collected on a weekly basis during the study period. Medical records were rated with the guidance of a rating protocol and data on OST were collected. The difference between baseline and the intervention period was assessed by a segmented regression. RESULTS: In this study, 371 patients were included. Compliance with the assessment process described in the prehospital CG was stable during the baseline period. Following the introduction of the CDSS, compliance rose significantly. The post-intervention slope was stable. The CDSS had no significant effect on OST. CONCLUSIONS: The use of CDSS in prehospital care has the ability to increase compliance with the assessment process of patients with a medical emergency. This study was unable to demonstrate any effects of OST.

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Environmental management is a complex task. The amount and heterogeneity of the data needed for an environmental decision making tool is overwhelming without adequate database systems and innovative methodologies. As far as data management, data interaction and data processing is concerned we here propose the use of a Geographical Information System (GIS) whilst for the decision making we suggest a Multi-Agent System (MAS) architecture. With the adoption of a GIS we hope to provide a complementary coexistence between heterogeneous data sets, a correct data structure, a good storage capacity and a friendly user’s interface. By choosing a distributed architecture such as a Multi-Agent System, where each agent is a semi-autonomous Expert System with the necessary skills to cooperate with the others in order to solve a given task, we hope to ensure a dynamic problem decomposition and to achieve a better performance compared with standard monolithical architectures. Finally, and in view of the partial, imprecise, and ever changing character of information available for decision making, Belief Revision capabilities are added to the system. Our aim is to present and discuss an intelligent environmental management system capable of suggesting the more appropriate land-use actions based on the existing spatial and non-spatial constraints.

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A tanulmány a vállalati működés során megjelenő környezetvédelmi intézkedések vállalaton belüli hasznainak rendszerezésével foglalkozik. A hagyományos vállalati számviteli rendszerben a környezetvédelem alapvetően a költségoldalon jelenik meg. Azonban a környezetvédelmi tevékenység vállalaton belül megjelenő hasznainak is fontos szerepe van környezetvédelmi intézkedésekkel, beruházásokkal kapcsolatos döntések meghozatalában. Ennek ellenére a környezeti hasznok a szakirodalomban elnagyoltan, valamint nem a teljes vállalatra vonatkozóan jelennek meg. Ezért a tanulmány célja, hogy a környezeti hasznok számviteli rendszerben való kimutatására egyfajta megoldást keressen. Az elemzés eredménye egy olyan új modell felállítása, amely képes a tulajdonosi érték koncepciójához szorosan kapcsolódva a vállalaton belüli környezeti hasznokat átfogóan kimutatni. Az újonnan felállított modell a hazai és a nemzetközi gyakorlatban is újdonságértékkel bír, és nagy előnye a vállalati gyakorlatban való alkalmazhatóság. --------- The main focus of this paper is the systematization of the environmental benefits within the company. The environmental benefits related to the company’s environmental action. Environmental protection appears in the accounting system mostly on the cost side. However, environmental benefits incurring within the company play an important role in the company’s environmental decision making processes. Despite these facts, environmental benefits are not analyzed in detail by the accounting literature and do not cover the whole activity of the company. Consequently, these paper aims to gain a possible demonstration of environmental benefits in the accounting system. The main outcome of this paper is a new model, able to comprehensively present the environmental benefits of the whole company. The theory on which the model is based is the shareholders’ value concept. The model has significant novelty both in the Hungarian and international practice. Another advantage of the model is that it can be integrated into the company’s accounting system.

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The paper presents the development of a decision support system for the management of geotechnical and environmental risks in oil pipelines using a geographical information system. The system covers a 48.5 km long section of the So Paulo to Brasilia (OSBRA) oil pipeline, which crosses three municipalities in the northeast region of the So Paulo state (Brazil) and represents an area of 205.8 km(2). The spatial database was created using geo-processing procedures, surface and intrusive investigations and geotechnical reports. The risk assessment was based mainly on qualitative models (relative numeric weights and multicriteria decision analysis) and considered pluvial erosion, slope movements, soil corrosion and third party activities. The maps were produced at a scale of 1:10,000.