Sales forecasting plays an important role in operating a business since it can be used to determine the required inventory level to meet consumer demand and avoid the problem of under/overstocking. Improving the accuracy of sales forecasting has become an important issue of operating a business. This study proposes a hybrid sales forecasting scheme by combining independent component analysis (I...

This paper describes an attempt to shed some light on road safety in Asia Pacific region by characterizing and assessing its road accidents. The relevant national road accident data were extracted from centralized data sources of international agencies. Due to data incompleteness and missing values, 21 Asia Pacific countries, presenting more than half of the world’s population, were selected fo...

Logistic regression was applied to accident-related data collected from traffic police records in order to examine the contribution of several variables to accident severity. A total of 560 subjects involved in serious accidents were sampled. Accident severity (the dependent variable) in this study is a dichotomous variable with two categories, fatal and non-fatal. Therefore, each of the subjec...

artificial neural networks (anns) are flexible computing frameworks and universal approximators that can be applied to a wide range of time series forecasting problems with a high degree of accuracy. however, despite of all advantages cited for artificial neural networks, they have data limitation and need to the large amount of historical data in order to yield accurate results. therefore, the...

The notion of representative statistical ensembles, correctly representing statistical systems, is strictly formulated. This notion allows for a proper description of statistical systems, avoiding inconsistencies in theory. As an illustration, a Bose-condensed system is considered. It is shown that a self-consistent treatment of the latter, using a representative ensemble, always yields a conse...

In weather and climate prediction studies it often turns out to be the case that the multi-model ensemble mean prediction has the best prediction skill scores. One possible explanation is that the major part of the model error is random and is averaged out in the ensemble mean. In the standard multi-model ensemble approach, the models are integrated in time independently and the predicted state...

Data from the Oxford Record Linkage Study have been used to describe rates of accident repetition for children aged under 5 years. As reflected by hospital admissions, accident rates for children who have already had one accident were approximately twice those of children of the same age and sex who had previously been accident free.

Numerous evaluation studies have reported large accident reductions when road accident blackspots are treated. A critical examination of these studies reveals that many of them do not account for the effects of well known confounding factors, like the regression-to-the-mean effect that is likely to occur at road accident blackspots. This paper shows that the more confounding factors evaluation ...

Log-linear modeling is advanced as a procedure to identify factors that underlie the relative frequency of occurrence of various accident characteristics, such as accident type, location, and severity. The method is centered on the estimation of saturated log-linear models for pairs of accident variables and determination of indices of association between categories of the variables. Using data...