24 resultados para Forecast Combination
Resumo:
Enhancing the resilience of local communities to weather extremes has gained significant interest over the years, amidst the increased intensity and frequency of such events. The fact that such weather extremes are forecast to further increase in number and severity in future has added extra weight to the importance of the issue. As a local community consists of a number of community groups such as households, businesses and policy makers, the actions of different community groups in combination will determine the resilience of the community as a whole. An important role has to be played by Small and Medium-sized Enterprises (SMEs); which is an integral segment of a local community in the UK, in this regard. While it is recognised that they are vital to the economy of a country and determines the prosperity of communities, they are increasingly vulnerable to effects of extreme weather. This paper discusses some of the exploratory studies conducted in the UK on SMEs and their ability to cope with extreme weather events, specifically flooding. Although a reasonable level of awareness of the risk was observed among the SMEs, this has not always resulted in increased preparedness even if they are located in areas at risk of flooding. The attitude and the motivation to change differed widely between SMEs. The paper presents schemas by which the SMEs can identify their vulnerability better so that they can be populated among a community of SMEs, which can be taken forward to inform policy making in this area. Therefore the main contribution the paper makes to the body of knowledge in the area is a novel way to communicate to SMEs on improving resilience against extreme weather, which will inform some of the policy making initiatives in the UK.
Resumo:
This paper presents a model for measuring personal knowledge development in online learning environments. It is based on Nonaka‘s SECI model of organisational knowledge creation. It is argued that Socialisation is not a relevant mode in the context of online learning and was therefore not covered in the measurement instrument. Therefore, the remaining three of SECI‘s knowledge conversion modes, namely Externalisation, Combination, and Internalisation were used and a measurement instrument was created which also examines the interrelationships between the three modes. Data was collected using an online survey, in which online learners report on their experiences of personal knowledge development in online learning environments. In other words, the instrument measures the magnitude of online learners‘ Externalisation and combination activities as well as their level of internalisation, which is the outcome of their personal knowledge development in online learning.
Resumo:
This study examines the information content of alternative implied volatility measures for the 30 components of the Dow Jones Industrial Average Index from 1996 until 2007. Along with the popular Black-Scholes and \model-free" implied volatility expectations, the recently proposed corridor implied volatil- ity (CIV) measures are explored. For all pair-wise comparisons, it is found that a CIV measure that is closely related to the model-free implied volatility, nearly always delivers the most accurate forecasts for the majority of the firms. This finding remains consistent for different forecast horizons, volatility definitions, loss functions and forecast evaluation settings.
Resumo:
Cleavage by the proteasome is responsible for generating the C terminus of T-cell epitopes. Modeling the process of proteasome cleavage as part of a multi-step algorithm for T-cell epitope prediction will reduce the number of non-binders and increase the overall accuracy of the predictive algorithm. Quantitative matrix-based models for prediction of the proteasome cleavage sites in a protein were developed using a training set of 489 naturally processed T-cell epitopes (nonamer peptides) associated with HLA-A and HLA-B molecules. The models were validated using an external test set of 227 T-cell epitopes. The performance of the models was good, identifying 76% of the C-termini correctly. The best model of proteasome cleavage was incorporated as the first step in a three-step algorithm for T-cell epitope prediction, where subsequent steps predicted TAP affinity and MHC binding using previously derived models.
Resumo:
Eight otherwise healthy diabetic volunteers took a daily antioxidant supplement consisting of vitamin E (200 IU), vitamin C (250 mg) and α-lipoic acid (90 mg) for a period of 6 weeks. Diabetic dapsone hydroxylamine-mediated methaemoglobin formation and resistance to erythrocytic thiol depletion was compared with age and sex-matched non-diabetic subjects. At time zero, methaemoglobin formation in the non-diabetic subjects was greater at all four time points compared with that of the diabetic subjects. Resistance to glutathione depletion was initially greater in non-diabetic compared with diabetic samples. Half-way through the study (3 weeks), there were no differences between the two groups in methaemoglobin formation and thiol depletion in the diabetic samples was now lower than the non-diabetic samples at 10 and 20 min. At 6 weeks, diabetic erythrocytic thiol levels remained greater than those of non-diabetics. HbA1c values were significantly reduced in the diabetic subjects at 6 weeks compared with time zero values. At 10 weeks, 4 weeks after the end of supplementation, the diabetic HbA1c values significantly increased to the point where they were not significantly different from the time zero values. Total antioxidant status measurement (TAS) indicated that diabetic plasma antioxidant capacity was significantly improved during antioxidant supplementation. Conversion of α-lipoic acid to dihydrolipoic acid (DHLA) in vivo led to potent interference in a standard fructosamine assay kit, negating its use in this study. This report suggests that triple antioxidant therapy in diabetic volunteers attenuates the in vitro experimental oxidative stress of methaemoglobin formation and reduces haemoglobin glycation in vivo. © 2003 Elsevier Science B.V. All rights reserved.
An improved conflicting evidence combination approach based on a new supporting probability distance
Resumo:
To avoid counter-intuitive result of classical Dempster's combination rule when dealing with highly conflict information, many improved combination methods have been developed through modifying the basic probability assignments (BPAs) of bodies of evidence (BOEs) by using a certain measure of the degree of conflict or uncertain information, such as Jousselme's distance, the pignistic probability distance and the ambiguity measure. However, if BOEs contain some non-singleton elements and the differences among their BPAs are larger than 0.5, the current conflict measure methods have limitations in describing the interrelationship among the conflict BOEs and may even lead to wrong combination results. In order to solve this problem, a new distance function, which is called supporting probability distance, is proposed to characterize the differences among BOEs. With the new distance, the information of how much a focal element is supported by the other focal elements in BOEs can be given. Also, a new combination rule based on the supporting probability distance is proposed for the combination of the conflicting evidences. The credibility and the discounting factor of each BOE are generated by the supporting probability distance and the weighted BOEs are combined directly using Dempster's rules. Analytical results of numerical examples show that the new distance has a better capability of describing the interrelationships among BOEs, especially for the highly conflicting BOEs containing non-singleton elements and the proposed new combination method has better applicability and effectiveness compared with the existing methods.
Resumo:
Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.
Resumo:
Binocular combination for first-order (luminancedefined) stimuli has been widely studied, but we know rather little about this binocular process for spatial modulations of contrast (second-order stimuli). We used phase-matching and amplitude-matching tasks to assess binocular combination of second-order phase and modulation depth simultaneously. With fixed modulation in one eye, we found that binocularly perceived phase was shifted, and perceived amplitude increased almost linearly as modulation depth in the other eye increased. At larger disparities, the phase shift was larger and the amplitude change was smaller. The degree of interocular correlation of the carriers had no influence. These results can be explained by an initial extraction of the contrast envelopes before binocular combination (consistent with the lack of dependence on carrier correlation) followed by a weighted linear summation of second-order modulations in which the weights (gains) for each eye are driven by the first-order carrier contrasts as previously found for first-order binocular combination. Perceived modulation depth fell markedly with increasing phase disparity unlike previous findings that perceived first-order contrast was almost independent of phase disparity. We present a simple revision to a widely used interocular gain-control theory that unifies first- and second-order binocular summation with a single principle-contrast-weighted summation-and we further elaborate the model for first-order combination. Conclusion: Second-order combination is controlled by first-order contrast.
Resumo:
Energy crops production is considered as environmentally benign and socially acceptable, offering ecological benefits over fossil fuels through their contribution to the reduction of greenhouse gases and acidifying emissions. Energy crops are subjected to persistent policy support by the EU, despite their limited or even marginally negative impact on the greenhouse effect. The present study endeavors to optimize the agricultural income generated by energy crops in a remote and disadvantageous region, with the assistance of linear programming. The optimization concerns the income created from soybean, sunflower (proxy for energy crop), and corn. Different policy scenarios imposed restrictions on the value of the subsidies as a proxy for EU policy tools, the value of inputs (costs of capital and labor) and different irrigation conditions. The results indicate that the area and the imports per energy crop remain unchanged, independently of the policy scenario enacted. Furthermore, corn cultivation contributes the most to iFncome maximization, whereas the implemented CAP policy plays an incremental role in uptaking an energy crop. A key implication is that alternative forms of motivation should be provided to the farmers beyond the financial ones in order the extensive use of energy crops to be achieved.