Improving load forecasting accuracy through combination of best forecasts

Neural network (NN) models have been widely used in the literature for short-term load forecasting. Their popularity is mainly due to their excellent learning and approximation capability. However, their forecasting performance significantly depends on several factors including initializing parameters, training algorithm, and NN structure. To minimize negative effects of these factors, this paper proposes a practically simple, yet effective and an efficient method to combine forecasts generated by NN models. The proposed method includes three main phases: (i) training NNs with different structures, (ii) selecting best NN models based on their forecasting performance for a validation set, and (iii) combination of forecasts for selected best NNs. Forecast combination is performed through calculating the mean of forecasts generated by best NN models. The performance of the proposed method is examined using real world data set. Comparative studies demonstrate that the accuracy of combined forecasts is significantly superior to those obtained from individual NN models.

Aggregation of Pi-based forecast to enhance prediction accuracy

In contrast to point forecast, prediction interval-based neural network offers itself as an effective tool to quantify the uncertainty and disturbances that associated with process data. However, single best neural network (NN) does not always guarantee to predict better quality of forecast for different data sets or a whole range of data set. Literature reported that ensemble of NNs using forecast combination produces stable and consistence forecast than single best NN. In this work, a NNs ensemble procedure is introduced to construct better quality of Pis. Weighted averaging forecasts combination mechanism is employed to combine the Pi-based forecast. As the key contribution of this paper, a new Pi-based cost function is proposed to optimize the individual weights for NN in combination process. An optimization algorithm, named simulated annealing (SA) is used to minimize the PI-based cost function. Finally, the proposed method is examined in two different case studies and compared the results with the individual best NNs and available simple averaging Pis aggregating method. Simulation results demonstrated that the proposed method improved the quality of Pis than individual best NNs and simple averaging ensemble method.

Application of air quality combination forecasting to Bogota

The bulk of existing work on the statistical forecasting of air quality is based on either neural networks or linear regressions, which are both subject to important drawbacks. In particular, while neural networks are complicated and prone to in-sample overfitting, linear regressions are highly dependent on the specification of the regression function. The present paper shows how combining linear regression forecasts can be used to circumvent all of these problems. The usefulness of the proposed combination approach is verified using both Monte Carlo simulation and an extensive application to air quality in Bogota, one of the largest and most polluted cities in Latin America. © 2014 Elsevier Ltd.

Bayesian model averaging of load demand forecasts from neural network models

Creating a set of a number of neural network (NN) models in an ensemble and accumulating them can achieve better overview capability as compared to single neural network. Neural network ensembles are designed to provide solutions to particular problems. Many researchers and academicians have adopted this NN ensemble technique, especially in machine learning, and has been applied in various fields of engineering, medicine and information technology. This paper present a robust aggregation methodology for load demand forecasting based on Bayesian Model Averaging of a set of neural network models in an ensemble. This paper estimate a vector of coefficient for individual NN models' forecasts using validation data-set. These coefficients, also known as weights, are equal to posterior probabilities of the models generating the forecasts. These BMA weights are then used in combining forecasts generated from NN models with test data-set. By comparing the Bayesian results with the Simple Averaging method, it was observed that benefits are obtained by utilizing an advanced method like BMA for forecast combinations.

Improving the quality of prediction intervals through optimal aggregation

Neural networks (NNs) are an effective tool to model nonlinear systems. However, their forecasting performance significantly drops in the presence of process uncertainties and disturbances. NN-based prediction intervals (PIs) offer an alternative solution to appropriately quantify uncertainties and disturbances associated with point forecasts. In this paper, an NN ensemble procedure is proposed to construct quality PIs. A recently developed lower-upper bound estimation method is applied to develop NN-based PIs. Then, constructed PIs from the NN ensemble members are combined using a weighted averaging mechanism. Simulated annealing and a genetic algorithm are used to optimally adjust the weights for the aggregation mechanism. The proposed method is examined for three different case studies. Simulation results reveal that the proposed method improves the average PI quality of individual NNs by 22%, 18%, and 78% for the first, second, and third case studies, respectively. The simulation study also demonstrates that a 3%-4% improvement in the quality of PIs can be achieved using the proposed method compared to the simple averaging aggregation method.

Systematic review and meta-analysis of evidence for increasing numbers of drugs in antiretroviral combination therapy

Objective: To assess the evidence for the effectiveness of increasing numbers of drugs in antiretroviral combination therapy.

Design: Systematic review, meta-analysis, and meta-regression of fully reported randomised controlled trials. All studies included compared quadruple versus triple therapy, triple versus double therapy, double versus monotherapy, or monotherapy versus placebo or no treatment.

Participants: Patients with any stage of HIV infection who had not received antiretroviral therapy.

Main outcome measures: Changes in disease progression or death (clinical outcomes); CD4 count and plasma viral load (surrogate markers).
Search strategy: Six electronic databases, including Medline, Embase, and the Cochrane Library, searched up to February 2001.

Results: 54 randomised controlled trials, most of good quality, with 66 comparison groups were included in the analysis. For both the clinical outcomes and surrogate markers, combinations with up to and including three (triple therapy) were progressively and significantly more effective. The odds ratio for disease progression or death for triple therapy compared with double therapy was 0.6 (95% confidence interval 0.5 to 0.8). Heterogeneity in effect sizes was present in many outcomes but was largely related to the drugs used and trial quality.

Conclusions: Evidence from randomised controlled trials supports the use of triple therapy. Research is needed on the effectiveness of quadruple therapies and the relative effectiveness of specific combinations of drugs.

Use of calcium or calcuim in combination with vitamin D supplementation to prevent fractures and bone loss in people aged 50 years and older: a meta-analysis

Background:  Whether calcium supplementation can reduce osteoporotic fractures is uncertain. We did a meta-analysis to include all the randomised trials in which calcium, or calcium in combination with vitamin D, was used to prevent fracture and osteoporotic bone loss.

Methods:  We identified 29 randomised trials (n=63 897) using electronic databases, supplemented by a hand-search of reference lists, review articles, and conference abstracts. All randomised trials that recruited people aged 50 years or older were eligible. The main outcomes were fractures of all types and percentage change of bone-mineral density from baseline. Data were pooled by use of a random-effect model.

Findings:  In trials that reported fracture as an outcome (17 trials, n=52 625), treatment was associated with a 12% risk reduction in fractures of all types (risk ratio 0·88, 95% CI 0·83–0·95; p=0·0004). In trials that reported bone-mineral density as an outcome (23 trials, n=41 419), the treatment was associated with a reduced rate of bone loss of 0·54% (0·35–0·73; p<0·0001) at the hip and 1·19% (0·76–1·61%; p<0·0001) in the spine. The fracture risk reduction was significantly greater (24%) in trials in which the compliance rate was high (p<0·0001). The treatment effect was better with calcium doses of 1200 mg or more than with doses less than 1200 mg (0·80 vs 0·94; p=0·006), and with vitamin D doses of 800 IU or more than with doses less than 800 IU (0·84 vs 0·87; p=0·03).

Interpretation:  Evidence supports the use of calcium, or calcium in combination with vitamin D supplementation, in the preventive treatment of osteoporosis in people aged 50 years or older. For best therapeutic effect, we recommend minimum doses of 1200 mg of calcium, and 800 IU of vitamin D (for combined calcium plus vitamin D supplementation).

The role of dualities in arbitrating continuity and change in forms of organizing

A substantial body of literature on new forms of organizing has forecast the end of bureaucracy. More recent empirical studies, however, indicate that high-performing organizations are adopting dual forms of organizing in which the controllability advantages associated with traditional forms work to complement and support the responsiveness attributes of new forms of organizing. The paradox is that, if organizations discard the key planning, co-ordinating and direction-setting mechanisms of traditional forms of organizing, they also remove the stabilizing dimensions of organizational form that are essential in periods of uncertainty and change. The challenge for organizations lies in learning how to manage the tensions or dualities between traditional and new forms of organizing, a process demanding the arbitration of continuity and change. This paper explores the concept of dualities and its salience in the management of organizing forms. First, the nature of dualities is explained; secondly, a set of characteristics is developed to describe the behaviour of dualities; and thirdly, suggestions are presented for arbitrating the tensions that exist in organizing form dualities. These three contributions are relevant because they signal the route to the effective creation and management of organizing form dualities, the benefit of which is the constructive combination of dynamic capabilities (underpinning innovation and responsiveness, the hallmarks of new forms of organizing) and operational capabilities (underpinning stability and efficiency, the hallmarks of traditional forms of organizing).

The effects of the opioid pharmacotherapies methadone, LAAM and buprenorphine, alone and in combination with alcohol, on simulated driving

While methadone is currently the primary pharmacotherapy used in the treatment of heroin dependence in Australia, levo-alpha-acetyl-methodol (LAAM) and buprenorphine are new pharmacotherapies that are being examined as alternatives to methadone maintenance treatment. The aim of this research is to consider the effects of the methadone, buprenorphine and LAAM, as used in maintenance pharmacotherapy for heroin dependence, upon simulated driving. Clients stabilised in methadone, LAAM and buprenorphine treatment programs for 3 months, and a control group of non-drug-using participants, took part in this study which involved operating a driving simulator over a 75 min period.

Two-year combination antibiotic therapy with clarithromycin, rifabutin, and clofazimine for Crohn's disease

Background & Aims: Mycobacterium avium subspecies paratuberculosis has been proposed as a cause of Crohn’s disease. We report a prospective, parallel, placebo-controlled, double-blind, randomized trial of 2 years of clarithromycin, rifabutin, and clofazimine in active Crohn’s disease, with a further year of follow-up. Methods: Two hundred thirteen patients were randomized to clarithromycin 750 mg/day, rifabutin 450 mg/day, clofazimine 50 mg/day or placebo, in addition to a 16-week tapering course of prednisolone. Those in remission (Crohn’s Disease Activity Index ≤150) at week 16 continued their study medications in the maintenance phase of the trial. Primary end points were the proportion of patients experiencing at least 1 relapse at 12, 24, and 36 months. Results: At week 16, there were significantly more subjects in remission in the antibiotic arm (66%) than the placebo arm (50%; P = .02). Of 122 subjects entering the maintenance phase, 39% taking antibiotics experienced at least 1 relapse between weeks 16 and 52, compared with 56% taking placebo (P = .054). At week 104, the figures were 26% and 43%, respectively (P = .14). During the following year, 59% of the antibiotic group and 50% of the placebo group relapsed (P = .54). Conclusions: Using combination antibiotic therapy with clarithromycin, rifabutin, and clofazimine for up to 2 years, we did not find evidence of a sustained benefit. This finding does not support a significant role for Mycobacterium avium subspecies paratuberculosis in the pathogenesis of Crohn’s disease in the majority of patients. Short-term improvement was seen when this combination was added to corticosteroids, most likely because of nonspecific antibacterial effects.

Image retrieval based on the combination of color and keyword

In this paper, color information and keyword information are combined for image retrieval. In detail, each image is divided into several blocks and then the color histograms of each block are derived. Users could feed back some annotations represented by keywords. Then, the keywords may spread in the image database so that both color-based and keyword-based retrieval could be utilized together. A prototype system shows that the proposed method is effective and efficient in performing image retrieval tasks.

Measuring expectations: forecast vs. ideal expectations. Does it really matter?

Consumer’s participation in service delivery is so central to cognition that it affects consumer’s quality evaluations. The study presented in this paper investigates the ways that visitor expectations change as a result of first hand experience with a service in the context of a major art exhibition. The research design allowed for two operational definitions of expectations, namely forecast and ideal expectations, in order to investigate differences between respondents’ pre and post experiences with a service. A total of 550 respondent visitors were interviewed during a major art exhibition, using two questionnaires delivered to two sub samples of respondents. The primary questionnaire was designed to capture recalled expectations after visitation while the parallel questionnaire captured forecast expectations prior to visitation and perceptions in the post experience phase. The findings suggest that forecast expectations were different to ideal expectations in both qualitative and quantitative ways and that these differences had important implications for perceptions of service quality. These differences can be explained, at least in part, by the way that expectations are formed and by the way that expectations are shaped by the actual visitation experience. For market researchers, the question of when and how to measure expectations has important implications for research design.

Dietary combination of soy with a probiotic or prebiotic food significantly reduces total and LDL cholesterol in mildly hypercholesterolaemic subjects

Objective: We hypothesized that a dietary combination of soy with either a probiotic (yoghurt) or a prebiotic (resistant starch) would result in enhanced lipid-lowering effects compared with a control soy diet, possibly via improvements in isoflavone bioavailability.

Subjects: Mildly hypercholesterolaemic subjects (men and post-menopausal women) older than 45 years were recruited via the local media. Thirty-six subjects commenced the study; five withdrew.

Results: Soy+probiotic significantly decreased total cholesterol (4.72.0%; P=0.038) and soy+prebiotic significantly decreased total and low-density lipoprotein cholesterol (5.51.6%; P=0.003 and 7.32.2%; P=0.005, respectively). The bioavailabilities of daidzein, genistein or equol were not affected by probiotic or prebiotic consumption or associated with lipid changes.

Conclusion: Dietary combination of soy with either a probiotic or a prebiotic resulted in significant lipid lowering, not related to isoflavone bioavailability.

The forecast quality of CBOE implied volatility indexes

We examine the forecast quality of Chicago Board Options Exchange (CBOE) implied volatility indexes based on the Nasdaq 100 and Standard and Poor's 100 and 500 stock indexes. We find that the forecast quality of CBOE implied volatilities for the S&P 100 (VXO) and S&P 500 (VIX) has improved since 1995. Implied volatilities for the Nasdaq 100 (VXN) appear to provide even higher quality forecasts of future volatility. We further find that attenuation biases induced by the econometric problem of errors in variables appear to have largely disappeared from CBOE volatility index data since 1995.