关键词： cost-effectiveness   implantable cardioverter-defibrillators   remote monitoring  

摘要： Background Remote monitoring of implantable cardioverter-defibrillators has been associated with reduced rates of all-cause rehospitalizations and mortality among device recipients, but long-term economic benefits have not been studied. Methods and Results An economic model was developed using the PREDICT RM database comparing outcomes with and without remote monitoring. The database included patients ages 65 to 89 who received a Boston Scientific device from 2006 to 2010. Parametric survival equations were derived for rehospitalization and mortality to predict outcomes over a maximum time horizon of 25 years. The analysis assessed rehospitalization, mortality, and the cost-effectiveness (expressed as the incremental cost per quality-adjusted life year) of remote monitoring versus no remote monitoring. Remote monitoring was associated with reduced mortality;average life expectancy and average quality-adjusted life years increased by 0.77 years and 0.64, respectively (6.85 life years and 5.65 quality-adjusted life years). When expressed per patient-year, remote monitoring patients had fewer subsequent rehospitalizations (by 0.08 per patient-year) and lower hospitalization costs (by $554 per patient year). With longer life expectancies, remote monitoring patients experienced an average of 0.64 additional subsequent rehospitalizations with increased average lifetime hospitalization costs of $2784. Total costs of outpatient and physician claims were higher with remote monitoring ($47 515 vs $42 792), but average per patient-year costs were lower ($6232 vs $6244). The base-case incremental cost-effectiveness ratio was $10 752 per quality-adjusted life year, making remote monitoring high-value care. Conclusion Remote monitoring is a cost-effective approach for the lifetime management of patients with implantable cardioverter-defibrillators.

关键词： Demand flexibility   Economic model predictive control   Artificial neural network   Optimal control   Experimental case study   Residential building  

摘要： Future building energy management systems will have to be capable of adapting to variation in the rate of production of energy from renewable sources. Controllers employing a model predictive control (MPC) framework can optimise and schedule energy usage based on the availability of renewably generated energy. In this paper, an MPC using artificial neural networks (ANNs) was implemented in a residential building. The ANN-MPC was successfully tested and demonstrated good performance predicting the building's energy consumption. The controller was then modified to function as an economic MPC (EMPC) to optimise demand flexibility (i.e., the ability to adapt energy demands to fluctuations in supply). The operational costs of energy usage were associated with this demand flexibility, which was represented by three flexibility indicators: flexibility factor, supply cover factor, and load cover factor. The results from a day-long test showed that these flexibility indicators were maximised (flexibility factor ranged from -0.88 to 0.67, supply cover factor from 0.04 to 0.13, and load cover factor from 0.07 to 0.16) when the EMPC controller's demand flexibility was compared to that of a conventional proportional-integral (PI) controller. The EMPC framework for demand flexibility can be used to regulate on-site energy generation, grid consumption, and grid feed-in and can thus serve as a basis for overall optimisation of the operation of heating systems to achieve greater demand flexibility. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： predictive control   stability   linear matrix inequalities   boilers   power plants   thermal power stations   fuzzy control   feedback   optimisation   power generation control   fuzzy set theory   linear feedback controller   approximate the system   boiler-turbine system control   economic index   fuzzy economic MPC   total power plant process   dynamic optimum   steady-state optimisation   HMPC architecture   dynamic tracking   low layer realises   economic optimisation   upper layer   hierarchical MPC architecture   power plant economy   plant thermal dynamic   fuzzy modelling technique   load tracking   effective method   fuzzy model predictive control   modern thermal power plant   fuzzy economic model predictive control  

摘要： In a modern thermal power plant, fuzzy model predictive control (MPC) is an effective method for realising load tracking and economy of boiler-turbine system, by using fuzzy modelling technique considering the plant thermal dynamic. The power plant economy is generally handled in a hierarchical MPC (HMPC) architecture, in which the upper layer realises the economic optimisation while the low layer realises the dynamic tracking. However, while this HMPC architecture realises the steady-state optimisation, it may neglect the dynamic optimum of the total power plant process. This study develops a fuzzy economic MPC to utilise the economic index directly as the cost function. It integrates economic optimisation and dynamic tracking of the boiler-turbine system control into one framework. Since a fuzzy model is used to approximate the system's non-linear behaviour, a linear feedback controller can be constituted for guaranteeing the feasibility and stability of the boiler-turbine system through linear matrix inequality. Simulation results are given to show the effectiveness of the proposed controller.

关键词： Economic model predictive control   robustness   periodic operation   real-time optimization   process optimization  

摘要： This study investigates the properties of a robust economic model predictive control (REMPC) algorithm with respect to rejection of disturbances in initial conditions and non-stationary disturbances, robust stabilization and closed-loop performance in the presence of model parameters' errors, and the enforcement of optimal economic periodic operations. A key characteristic of the algorithm is that it enforces robustness to model errors without requiring terminal conditions (unless periodic operation is desired) and instead a set-point trajectory is calculated at each time interval. Robust stability and convergence to the calculated set-point trajectory are enforced online by a set of constraints. Three case studies are used to illustrate the closed-loop performance of the REMPC algorithm for reactor operation under different conditions. The algorithm is shown to preserve stability in the presence of model parameters' mismatch. In the face of disturbances, the algorithm leads to higher profits when a variable set-point is used compared to a fixed one. Furthermore, the periodic operation obtained through the application of the robust algorithm confers an improved average cost compared to steady-state operation.

关键词： 计量经济模型   人口迁移   多重共线性   人口数量   拟合优度  

摘要： 从计量经济学模型的设定入手,研究城市人口数量的问题,选取GDP、农村人口数量、城市建成区面积、公共交通车辆运营数为影响因素,建立计量经济学模型。针对各影响因素之间存在的多重共线性问题,进行进一步研究分析,最终对模型进行修正并对其提出可行的发展政策。

关键词： 经济发展   驱动力   需求   经济模型   经济循环  

摘要： 社会的发展程度常常用经济指标作为衡量标准,寻找长期稳定的经济发展原始驱动力一直是政府、经济学家和企业家们思考的问题。经过多年的工作经历和研究成果,“需求”是经济发展的第一驱动力。人们在不同时期、不同环境、不同的条件下,需求会发生变化,用不同的形式满足需求,形成了多样化的自由交易行为,以此构成市场经济的根基。本文分析了需求产生或形成的方式,以及解决需求的方法,充分论证了围绕需求解决才能获得稳定的经济发展机会,并给出了以需求为导向的“需求经济循环”模型。依照此模型,可以为政府和企业打开突破经济发展窗口的钥匙。

关键词： 大学排名   科研经费   城市排名   生源质量   联立方程组  

摘要： 根据2009-2017武书连大学排名、高考志愿填报系统,华顿经济研究院《中国百强城市排行榜》,电子科大就业质量报告,教育部《高等学校科技统计资料汇编》,高等教育发展指标数据平台等数据,选择成都市综合排名、电科毕业5年后平均薪酬、电科科研经费支出、高层次人才排名作为解释变量,对电子科大当年排名及生源质量建立联立方程组模型。经过拟合,线性分析,模型的检验估计得到了最终模型。利用该模型对电子科大排名与生源质量之间的关系进行分析。通过增加人才招揽力度,加大学校城市宣传等方式可进一步提高生源质量。生源质量的提高同时能提升学校的排名名次。

关键词： Short food supply chain   Economic organisation   Trajectories   Participation   Case study  

摘要： While a number of works question the alterity of alternative food chains, little has been said about the social processes under which new economic models are, or may be, developed within the broader movement around `short food supply chains' (SFCs) in Europe. Considering SFCs as economic organisations, we propose an analytical framework based on New Economic Sociology and Convention Theory, enriched by Social and Solidarity Economics, to capture the social construction of new economic models in such chains. We apply this framework to two case studies: an open-air market promoting short food supply chains in France, and a partnership between an agricultural cooperative and several solidarity purchase groups (GAS) in Italy. Analysing the trajectories of the two initiatives, we highlight the processes through which new economic models are jointly built via interactions between different actors. Our results open two lines of discussion: one concerning the 'new economic models' that emerge from the two cases, a second regarding the actors' participation in elaborating and enacting these new models.

关键词： Technology diffusion   Adjustment costs   Computable general equilibrium model   Energy   Climate policy  

摘要： Considerations regarding the roles of advanced technologies are crucial in energy-economic modeling, as these technologies, while usually not yet commercially viable, could substitute for fossil energy when favorable policies are in place. To improve the representation of the penetration of advanced technologies in energy-economic models, we present a formulation that is parameterized based on observations, while capturing elements of rent and real adjustment cost increases if high demand due to a large policy shock suddenly appears. The formulation is applied to a global computable general equilibrium model to explore the role of low-carbon alternatives in the electric power sector. While other modeling approaches often adopt specific constraints on expansion, our approach is based on the assumption and observation that these constraints are not absolute, and how fast advanced technologies will expand is endogenous to economic incentives. The policy simulations, while not intended to represent realistic price paths, are designed to illustrate the response of our technology diffusion approach under sudden increased demand for advanced technologies. (C) 2019 The Author(s). Published by Elsevier B.V.