We investigate the eigenvalues statistics of ensembles of normal randommatrices when their order N tends to infinite. In the model the eigenvalues have uniform density within a region determined by a simple analytic polynomial curve. We study the conformal deformations of normal random ensembles to Hermitian random ensembles and give sufficient conditions for the latter to be a Wigner ensemble.

We describe a method to improve detection of disease outbreaks in pre-diagnostic time series data. The method uses multiple forecasters and learns the linear combination to minimize the expected squared error of the next day's forecast. This combination adaptively changes over time. This adaptive ensemble combination is used to generate a disease alert score for each day, using a separate multi...

abstract one of the major factors on the amount of water resources is river flow which is so dependent to the hydrologic and meteorologic phenomena. simulation and forecasting of river flow makes the decision maker capable to effectively manage the water resources projects. so, simulation and forecasting models such as artificial neural networks (anns) are commonly used for simulation and predi...

RÉSUMÉ. Cet article présente un système pour transformer, de façon automatique, des programmes écrits en C--, un langage impératif simple, en un ensemble d’équations du premier ordre. Cet ensemble d’équations utilisé pour représenter un programme C-a une signification mathématique précise et les techniques standards de mécanisation du raisonnement équationnel peuvent être déployées pour vérifie...

In this work we introduce a forecasting model with which we participated in the NN5 forecasting competition (the forecasting of 111 time series representing daily cash withdrawal amounts at ATM machines). The main idea of this ∗Accepted for publication in International Journal of Forecasting. Expected to appear in 2011.

Load forecasting in power systems is an important subject and has been studied from different points of view in order to achieve better load forecasting results. ”Ius paper will address one of the challenges in spatial load forecasting area urban re-development, and present a theory and methodology to incorporate urban re-development into spatial load forecasting considerations.

The forecasting of intermittent demand is a difficult task because of the irregular behavior of the demand process. As a result, the selection of an effective forecasting technique can be challenging. We present an object-oriented software framework for intermittent demand forecasting and inventory analysis. The object-oriented structure of this framework allows easy implementation and integrat...

We examine the relation between the importance for firms to meet external performance benchmarks and the role of internal forecasting and misreporting for increasing the likelihood of meeting benchmarks. Drawing on survey data from investment centers, we hypothesize and find that the importance of meeting benchmarks is positively associated with the sophistication of firms’ internal forecasting...

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...

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...