868 resultados para Uncertain demand
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A framework for assessing the robustness of long-duration repetitive orchestrations in uncertain evolving environments is proposed. The model assumes that service-based evaluation environments are stable over short time-frames only; over longer periods service-based environments evolve as demand fluctuates and contention for shared resources varies. The behaviour of a short-duration orchestration E in a stable environment is assessed by an uncertainty profile U and a corresponding zero-sum angel-daemon game Γ(U) [2]. Here the angel-daemon approach is extended to assess evolving environments by means of a subfamily of stochastic games. These games are called strategy oblivious because their transition probabilities are strategy independent. It is shown that the value of a strategy oblivious stochastic game is well defined and that it can be computed by solving a linear system. Finally, the proposed stochastic framework is used to assess the evolution of the Gabrmn IT system.
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The economic and financial crisis in Europe is affecting the financing of long-term infrastructure investment. There are multiple clearly identifiable channels: reduced demand for long-term investment, a tightening prudential framework for lending, upward adjustment of risk perception, complex transition of the financial system, and increasing macroeconomic, sovereign and regulatory risk. Some of the identified channels are potentially dangerous spillovers from the crisis that entail the risk of a downward spiral (eg increasing regulatory risk), while others are efficient market responses (eg reduced investment demand, correction of pricing of risk). Consequently, public policy instruments should not address the accessibility of long-term finance per se, but should explicitly target the critical channels.
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Demands are one of the most uncertain parameters in a water distribution network model. A good calibration of the model demands leads to better solutions when using the model for any purpose. A demand pattern calibration methodology that uses a priori information has been developed for calibrating the behaviour of demand groups. Generally, the behaviours of demands in cities are mixed all over the network, contrary to smaller villages where demands are clearly sectorised in residential neighbourhoods, commercial zones and industrial sectors. Demand pattern calibration has a final use for leakage detection and isolation. Detecting a leakage in a pattern that covers nodes spread all over the network makes the isolation unfeasible. Besides, demands in the same zone may be more similar due to the common pressure of the area rather than for the type of contract. For this reason, the demand pattern calibration methodology is applied to a real network with synthetic non-geographic demands for calibrating geographic demand patterns. The results are compared with a previous work where the calibrated patterns were also non-geographic.
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New business and technology platforms are required to sustainably manage urban water resources [1,2]. However, any proposed solutions must be cognisant of security, privacy and other factors that may inhibit adoption and hence impact. The FP7 WISDOM project (funded by the European Commission - GA 619795) aims to achieve a step change in water and energy savings via the integration of innovative Information and Communication Technologies (ICT) frameworks to optimize water distribution networks and to enable change in consumer behavior through innovative demand management and adaptive pricing schemes [1,2,3]. The WISDOM concept centres on the integration of water distribution, sensor monitoring and communication systems coupled with semantic modelling (using ontologies, potentially connected to BIM, to serve as intelligent linkages throughout the entire framework) and control capabilities to provide for near real-time management of urban water resources. Fundamental to this framework are the needs and operational requirements of users and stakeholders at domestic, corporate and city levels and this requires the interoperability of a number of demand and operational models, fed with data from diverse sources such as sensor networks and crowsourced information. This has implications regarding the provenance and trustworthiness of such data and how it can be used in not only the understanding of system and user behaviours, but more importantly in the real-time control of such systems. Adaptive and intelligent analytics will be used to produce decision support systems that will drive the ability to increase the variability of both supply and consumption [3]. This in turn paves the way for adaptive pricing incentives and a greater understanding of the water-energy nexus. This integration is complex and uncertain yet being typical of a cyber-physical system, and its relevance transcends the water resource management domain. The WISDOM framework will be modeled and simulated with initial testing at an experimental facility in France (AQUASIM – a full-scale test-bed facility to study sustainable water management), then deployed and evaluated in in two pilots in Cardiff (UK) and La Spezia (Italy). These demonstrators will evaluate the integrated concept providing insight for wider adoption.
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This paper presents a method for calculating the power flow in distribution networks considering uncertainties in the distribution system. Active and reactive power are used as uncertain variables and probabilistically modeled through probability distribution functions. Uncertainty about the connection of the users with the different feeders is also considered. A Monte Carlo simulation is used to generate the possible load scenarios of the users. The results of the power flow considering uncertainty are the mean values and standard deviations of the variables of interest (voltages in all nodes, active and reactive power flows, etc.), giving the user valuable information about how the network will behave under uncertainty rather than the traditional fixed values at one point in time. The method is tested using real data from a primary feeder system, and results are presented considering uncertainty in demand and also in the connection. To demonstrate the usefulness of the approach, the results are then used in a probabilistic risk analysis to identify potential problems of undervoltage in distribution systems. (C) 2012 Elsevier Ltd. All rights reserved.
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This paper addresses current changes in the highly diverse European landscape, and the way these transitions are being treated in policy and landscape management in the fragmented, heterogeneous and dynamic context of today’s Europe. It appears that intersecting driving forces are increasing the complexity of European landscapes and causing polarising developments in agricultural land use, biodiversity conservation and cultural landscape management. On the one hand, multifunctional rural landscapes, especially in peri-urban regions, provide services and functions that serve the citizens in their demand for identity, support their sense of belonging and offer opportunities for recreation and involvement in practical landscape management. On the other hand, industrial agricultural production on increasingly large farms produces food, feed, fibre and energy to serve expanding international markets with rural live ability and accessibility as a minor issue. The intermediate areas of traditionally dominant small and family farms in Europe seem to be gradually declining in profitability. The paper discusses the potential of a governance approach that can cope with the requirement of optimising land-sharing conditions and community-based landscape development, while adapting to global market conditions.
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This paper proposes a new approach for delay-dependent robust H-infinity stability analysis and control synthesis of uncertain systems with time-varying delay. The key features of the approach include the introduction of a new Lyapunov–Krasovskii functional, the construction of an augmented matrix with uncorrelated terms, and the employment of a tighter bounding technique. As a result, significant performance improvement is achieved in system analysis and synthesis without using either free weighting matrices or model transformation. Examples are given to demonstrate the effectiveness of the proposed approach.
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Introduction: The demand for emergency health services (EHS), both in the prehospital (ambulance) and hospital (emergency departments) settings, is growing rapidly in Australia. Broader health system changes have reduced available health infrastructure, particularly hospital beds, resulting in reduced access to and congestion of the EHS as demonstrated by longer waiting times and ambulance “ramping”. Ambulance ramping occurring when patients have a prolonged wait on the emergency vehicle due to the unavailability of hospital beds. This presentation will outline the trends in EHS demand in Queensland compared with the rest of Australia and factors that appear to be contributing to the growth in demand. Methods: Secondary analysis was conducted using data from publicly available sources. Data from the Queensland Ambulance Service and Queensland Health Emergency Department Information System (EDIS) also were analyzed. Results: The demand for ambulance services and emergency departments has been increasing at 8% and 4% per year over the last decade, respectively; while accessible hospital beds have reduced by almost 10% contributing to the emergency department congestion and possibly contributing to the prehospital demand. While the increase in the proportion of the elderly population seems to explain a great deal of the demand for EHS, other factors also influence this growth including patient characteristics, institutional and societal factors, economic, EHS arrangements, and clinical factors. Conclusions: Overcrowding of facilities that provide EHS are causing considerable community concern. This overcrowding is caused by the growing demand and reduced access. The causes of this growing demand are complex, and require further detailed analysis in order to quantify and qualify these causes in order to provide a resilient foundation of evidence for future policy direction.
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Background: There are indications that pre-hospital emergency care and management of patients can help reduce the demand for hospital emergency departments (EDs). Ambulance services play a significant role at this stage of care. In 2003, the Queensland Government introduced a Community Ambulance Cover (CAC) levy in return for a free ambulance service at the point of access to all Queenslanders. This may have led to the impression in consumers of an entitlement to free ambulance services under any circumstances regardless of the urgency of the matter which may have in turn contributed to the crowding of EDs in Queensland. Objectives: This paper aims to answer the following questions: - How many patients arrive at hospital EDs by ambulance in Queensland, compared to other modes of arrival? - How has this changed over time, particularly after the CAC introduction in 2003? What percentage of ambulance arrivals are urgent ED patients? - Has the perceived free ambulance services created extra demand for EDs in Queensland, compared with other Australian jurisdictions that charge patients for ambulance services? Methods: We will secondary analyse the data from sources such as Queensland Ambulance Services, Department of Health and Australian Bureau of Statistics to answer the research questions. Findings and Conclusions Queensland has the highest utilization rate of ambulance services (about 18% in 2007-08) and the highest annual growth rate in demand for these services (7.7% on average since 2000-01), well above the population growth. On the other hand, the proportion of ED patients arriving by ambulance in Queensland has increased by about 4% annually. However, when compared with other states and territories with charge at the point of access, it seems that the growth in demand for EDs cannot be explained solely or mainly by CAC or ambulance utilisation in Queensland.
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This paper investigates the robust H∞ control for Takagi-Sugeno (T-S) fuzzy systems with interval time-varying delay. By employing a new and tighter integral inequality and constructing an appropriate type of Lyapunov functional, delay-dependent stability criteria are derived for the control problem. Because neither any model transformation nor free weighting matrices are employed in our theoretical derivation, the developed stability criteria significantly improve and simplify the existing stability conditions. Also, the maximum allowable upper delay bound and controller feedback gains can be obtained simultaneously from the developed approach by solving a constrained convex optimization problem. Numerical examples are given to demonstrate the effectiveness of the proposed methods.