99 resultados para BENCHMARK


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In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence of plant uncertainties and input–output constraints. There is no requirement that the plant should be open-loop stable and the analysis is valid for general forms of non-linear system representation including the case out when the problem is constraint-free. The effectiveness of controllers designed according to the algorithm analyzed in this paper is demonstrated on a recognized benchmark problem and on a simulation of a continuous-stirred tank reactor (CSTR). In both examples a radial basis function neural network is employed as the non-linear system model.

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Although in several EU Member States many public interventions have been running for the prevention and/or management of obesity and other nutrition-related health conditions, few have yet been formally evaluated. The multidisciplinary team of the EATWELL project will gather benchmark data on healthy eating interventions in EU Member States and review existing information on the effectiveness of interventions using a three-stage procedure (i) Assessment of the intervention's impact on consumer attitudes, consumer behaviour and diets; (ii) The impact of the change in diets on obesity and health and (iii) The value attached by society to these changes, measured in life years gained, cost savings and quality-adjusted life years. Where evaluations have been inadequate, EATWELL will gather secondary data and analyse them with a multidisciplinary approach incorporating models from the psychology and economics disciplines. Particular attention will be paid to lessons that can be learned from private sector that are transferable to the healthy eating campaigns in the public sector. Through consumer surveys and workshops with other stakeholders, EATWELL will assess the acceptability of the range of potential interventions. Armed with scientific quantitative evaluations of policy interventions and their acceptability to stakeholders, EATWELL expects to recommend more appropriate interventions for Member States and the EU, providing a one-stop guide to methods and measures in interventions evaluation, and outline data collection priorities for the future.

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Associative memory networks such as Radial Basis Functions, Neurofuzzy and Fuzzy Logic used for modelling nonlinear processes suffer from the curse of dimensionality (COD), in that as the input dimension increases the parameterization, computation cost, training data requirements, etc. increase exponentially. Here a new algorithm is introduced for the construction of a Delaunay input space partitioned optimal piecewise locally linear models to overcome the COD as well as generate locally linear models directly amenable to linear control and estimation algorithms. The training of the model is configured as a new mixture of experts network with a new fast decision rule derived using convex set theory. A very fast simulated reannealing (VFSR) algorithm is utilized to search a global optimal solution of the Delaunay input space partition. A benchmark non-linear time series is used to demonstrate the new approach.

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In a world of almost permanent and rapidly increasing electronic data availability, techniques of filtering, compressing, and interpreting this data to transform it into valuable and easily comprehensible information is of utmost importance. One key topic in this area is the capability to deduce future system behavior from a given data input. This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency. Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.

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Based on integrated system optimisation and parameter estimation a method is described for on-line steady state optimisation which compensates for model-plant mismatch and solves a non-linear optimisation problem by iterating on a linear - quadratic representation. The method requires real process derivatives which are estimated using a dynamic identification technique. The utility of the method is demonstrated using a simulation of the Tennessee Eastman benchmark chemical process.

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We explore the potential for making statistical decadal predictions of sea surface temperatures (SSTs) in a perfect model analysis, with a focus on the Atlantic basin. Various statistical methods (Lagged correlations, Linear Inverse Modelling and Constructed Analogue) are found to have significant skill in predicting the internal variability of Atlantic SSTs for up to a decade ahead in control integrations of two different global climate models (GCMs), namely HadCM3 and HadGEM1. Statistical methods which consider non-local information tend to perform best, but which is the most successful statistical method depends on the region considered, GCM data used and prediction lead time. However, the Constructed Analogue method tends to have the highest skill at longer lead times. Importantly, the regions of greatest prediction skill can be very different to regions identified as potentially predictable from variance explained arguments. This finding suggests that significant local decadal variability is not necessarily a prerequisite for skillful decadal predictions, and that the statistical methods are capturing some of the dynamics of low-frequency SST evolution. In particular, using data from HadGEM1, significant skill at lead times of 6–10 years is found in the tropical North Atlantic, a region with relatively little decadal variability compared to interannual variability. This skill appears to come from reconstructing the SSTs in the far north Atlantic, suggesting that the more northern latitudes are optimal for SST observations to improve predictions. We additionally explore whether adding sub-surface temperature data improves these decadal statistical predictions, and find that, again, it depends on the region, prediction lead time and GCM data used. Overall, we argue that the estimated prediction skill motivates the further development of statistical decadal predictions of SSTs as a benchmark for current and future GCM-based decadal climate predictions.

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Van der Heijden’s ENDGAME STUDY DATABASE IV, HhdbIV, is the definitive collection of 76,132 chess studies. In each one, White is to achieve the stipulated goal, win or draw: study solutions should be essentially unique with minor alternatives at most. In this second note on the mining of the database, we use the definitive Nalimov endgame tables to benchmark White’s moves in sub-7-man chess against this standard of uniqueness. Amongst goal-compatible mainline positions and goal-achieving moves, we identify the occurrence of absolutely unique moves and analyse the frequency and lengths of absolutely-unique-move sequences, AUMSs. We identify the occurrence of equi-optimal moves and suboptimal moves and refer to a defined method for classifying their significance.

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Depreciation is a key element of understanding the returns from and price of commercial real estate. Understanding its impact is important for asset allocation models and asset management decisions. It is a key input into well-constructed pricing models and its impact on indices of commercial real estate prices needs to be recognised. There have been a number of previous studies of the impact of depreciation on real estate, particularly in the UK. Law (2004) analysed all of these studies and found that the seemingly consistent results were an illusion as they all used a variety of measurement methods and data. In addition, none of these studies examined impact on total returns; they examined either rental value depreciation alone or rental and capital value depreciation. This study seeks to rectify this omission, adopting the best practice measurement framework set out by Law (2004). Using individual property data from the UK Investment Property Databank for the 10-year period between 1994 and 2003, rental and capital depreciation, capital expenditure rates, and total return series for the data sample and for a benchmark are calculated for 10 market segments. The results are complicated by the period of analysis which started in the aftermath of the major UK real estate recession of the early 1990s, but they give important insights into the impact of depreciation in different segments of the UK real estate investment market.

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The question as to whether active management adds any value above that of the funds investment policy is one of continual interest to investors. In order to investigate this issue in the UK real estate market we examine a number of related questions. First, how much return variability is explained by investment policy? Second, how similar are the policies across funds? Third, how much of a fund’s return is determined by investment policy? Finally, how was this added value achieved? Using data for 19 real estate funds we find that investment policy explains less than half of the variability in returns over time, nothing of the variation across funds and that more than 100% of a level of return is attributed to investment policy. The results also show UK real estate fund focus exclusively on trying to pick winners to add value and that in pursuit of active return fund mangers incur high tracking error risk, consequently, successful active management is very difficult to achieve. In addition, the results are dependent on the benchmark used to represent the investment policy of the fund. Nonetheless, active management can indeed add value to a real estate funds performance. This is the good news. The bad news is adding value is much more difficult to achieve than is generally accepted.

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Built environment programmes in West African universities; and research contributions from West Africa in six leading international journals and proceedings of the WABER conference are explored. At least 20 universities in the region offer degree programmes in Architecture (86% out of 23 universities); Building (57%); Civil Engineering (67%); Estate Management (52%); Quantity Surveying (52%); Surveying and Geoinformatics (55%); Urban and Regional Planning (67%). The lecturer-student ratio on programmes is around 1:25 compared to the 1:10 benchmark for excellence. Academics who teach on the programmes are clearly research active with some having published papers in leading international journals. There is, however, plenty of scope for improvement particularly at the highest international level. Out of more than 5000 papers published in six leading international peer-reviewed journals since each of them was established, only 23 of the papers have come from West Africa. The 23 papers are published by 28 academics based in 13 universities. Although some academics may publish their work in the plethora of journals that have proliferated in recent years, new generation researchers are encouraged to publish in more established journals. The analyses of 187 publications in the WABER conference proceedings revealed 18 research-active universities. Factors like quality of teaching, research and lecturer-student ratio, etc count in the ranking of universities. The findings lay bare some of the areas that should be addressed to improve the landscape of higher education in West Africa.

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The reduction of portfolio risk is important to all investors but is particularly important to real estate investors as most property portfolios are generally small. As a consequence, portfolios are vulnerable to a significant risk of under-performing the market, or a target rate of return and so investors may be exposing themselves to greater risk than necessary. Given the potentially higher risk of underperformance from owning only a few properties, we follow the approach of Vassal (2001) and examine the benefits of holding more properties in a real estate portfolio. Using Monte Carlo simulation and the returns from 1,728 properties in the IPD database, held over the 10-year period from 1995 to 2004, the results show that increases in portfolio size offers the possibility of a more stable and less volatile return pattern over time, i.e. down-side risk is diminished with increasing portfolio size. Nonetheless, increasing portfolio size has the disadvantage of restricting the probability of out-performing the benchmark index by a significant amount. In other words, although increasing portfolio size reduces the down-side risk in a portfolio, it also decreases its up-side potential. Be that as it may, the results provide further evidence that portfolios with large numbers of properties are always preferable to portfolios of a smaller size.

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Research in the late 1980s showed that in many corporate real estates users were not fully aware of the full extent of their property holdings. In many cases, not only was the value of the holdings unknown, but there was uncertainty over the actual extent of ownership within the portfolio. This resulted in a large number of corporate occupiers reviewing their property holdings during the 1990s, initially to create a definitive asset register, but also to benefit from an more efficient use of space. Good management of corporately owned property assets is of equal importance as the management of other principal resources within the company. A comprehensive asset register can be seen as the first step towards a rational property audit. For the effective, efficient and economic delivery of services, it is vital that all property holdings are utilised to the best advantage. This requires that the property provider and the property user are both fully conversant with the value of the property holding and that an asset/internal rent/charge is made accordingly. The advantages of internal rent charging are twofold. Firstly, it requires the occupying department to “contribute” an amount to the business equivalent to the open market rental value of the space that it occupies. This prevents the treating of space as a free good and, as individual profit centres, each department will then rationalise its holdings to minimise its costs. The second advantage is from a strategic viewpoint. By charging an asset rent, the holding department can identify the performance of its real estate holdings. This can then be compared to an internal or external benchmark to help determine whether the company has adopted the most efficient tenure pattern for its properties. This paper investigates the use of internal rents by UK-based corporate businesses and explains internal rents as a form of transfer pricing in the context of management and responsibility accounting. The research finds that the majority of charging organisations introduced internal rents primarily to help calculate true profits at the business unit level. However, less than 10% of the charging organisations introduced internal rents primarily to capture the return on assets within the business. There was also a sizeable element of the market who had no plans to introduce internal rents. Here, it appears that, despite academic and professional views that internal rents are beneficial in improving the efficient use of property, opinion at the business and operational level has not universally accepted this proposition.

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This account summarizes recent work by us and others on the development of ligands for the separation of actinides from lanthanides contained in nuclear waste streams in the context of a future European strategy for nuclear waste management. The current status of actinide/lanthanide separations worldwide is briefly discussed, and the synthesis, development, and testing of different classes of heterocyclic soft N- and S-donor ligands in Europe over the last 20 years is presented. This work has led to the current benchmark ligand that displays many of the desirable qualities for industrial use. The improvement of radiolytic stability through ligand design is also discussed.

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This paper investigates the price effects of environmental certification on commercial real estate assets. It is argued that there are likely to be three main drivers of price differences between certified and non-certified buildings. First, certified buildings offer a bundle of benefits to occupiers relating to business productivity, image and occupancy costs. Second, due to these occupier benefits, certified buildings can result in higher rents and lower holding costs for investors. Third, certified buildings may require a lower risk premium. Drawing upon the CoStar database of US commercial real estate assets, hedonic regression analysis is used to measure the effect of certification on both rent and price. We first estimate the rental regression for a sample of 110 LEED and 433 Energy Star as well as several thousand benchmark buildings to compare the sample to. The results suggest that, compared to buildings in the same metropolitan region, certified buildings have a rental premium and that the more highly rated that buildings are in terms of their environmental impact, the greater the rental premium. Furthermore, based on a sample of transaction prices for 292 Energy Star and 30 LEED-certified buildings, we find price premia of 10% and 31% respectively compared to non-certified buildings in the same metropolitan area

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This paper provides evidence regarding the risk-adjusted performance of 19 UK real estate funds in the UK, over the period 1991-2001. Using Jensen’s alpha the results are generally favourable towards the hypothesis that real estate fund managers showed superior risk-adjusted performance over this period. However, using three widely known parametric statistical procedures to jointly test for timing and selection ability the results are less conclusive. The paper then utilises the meta-analysis technique to further examine the regression results in an attempt to estimate the proportion of variation in results attributable to sampling error. The meta-analysis results reveal strong evidence, across all models, that the variation in findings is real and may not be attributed to sampling error. Thus, the meta-analysis results provide strong evidence that on average the sample of real estate funds analysed in this study delivered significant risk-adjusted performance over this period. The meta-analysis for the three timing and selection models strongly indicating that this out performance of the benchmark resulted from superior selection ability, while the evidence for the ability of real estate fund managers to time the market is at best weak. Thus, we can say that although real estate fund managers are unable to outperform a passive buy and hold strategy through timing, they are able to improve their risk-adjusted performance through selection ability.