Uncertain data is believed to be an important issue in building up a prediction model. The main objective in the time series uncertainty analysis is to formulate uncertain data in order to gain knowledge and fit low dimensional model prior to a prediction task. This paper discusses the performance of a number of techniques in dealing with uncertain data specifically those which solve uncertain ...

Is public R&D spending complementary and thus “additional” to private R&D spending, or does it substitute for and tend to “crowd out” private R&D? Conflicting answers are given to this question. We survey the body of available econometric evidence accumulated over the past 35 years. A framework for analysis of the problem is developed to help organize and summarize the findings of econometric s...

The British Geological Survey has operated a World Data Centre for Geomagnetism since 1966. Geomagnetic time-series data from around 280 observatories worldwide at a number of time resolutions are held along with various magnetic survey, model, and activity index data. The operation of this data centre provides a valuable resource for the geomagnetic research community. The operation of the WDC...

In recent years, extensive literature on the Environmental Kuznets Curve leading to optimistic policy conclusions has attracted great attention. However, the underlying cross-section estimations are not very reliable. Accordingly, this contribution uses time series data for a single country with good data quality: Germany. With a specification that includes all theoretical variations and differ...

background and objective: scorpion sting and snakebite are the important problems in some area such as iran that must be addressed. this study was to investigate temporal pattern of scorpion sting and snakebite incidence in patients referred to masjedsoleiman’s main hospital, during 24 months from 21 march 2008 to 20 march 2009. materials and methods: it was an analytical study to scrutiny of m...

with rapid development in information gathering technologies and access to large amounts of data, we always require methods for data analyzing and extracting useful information from large raw dataset and data mining is an important method for solving this problem. clustering analysis as the most commonly used function of data mining, has attracted many researchers in computer science. because o...

As with most computer science problems, representation of the data is the key to ecient and eective solutions. Piecewise linear representation has been used for the representation of the data. This representation has been used by various researchers to support clustering, classication, indexing and association rule mining of time series data. A variety of algorithms have been proposed to obtain...

background road traffic accidents and their related deaths have become a major concern, particularly in developing countries. iran has adopted a series of policies and interventions to control the high number of accidents occurring over the past few years. in this study we used a time series model to understand the trend of accidents, and ascertain the viability of applying arima models on data...