Time Series Modeling
Takagi interpolation problem as time series modeling
... Abstract— In this paper, we consider Takagi interpolation probelm, in which a rational function interpolating given complex pairs with norm constraint have unstable poles, as time series modeling in ...
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TIME SERIES MODELING OF TROPICAL RIVER RUNOFF
... sophisticated modeling and simulation methods for explaination and use. Time Series modeling allows runoff data analysis and can be used as forecasting ...real time river ...
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Feature Selection for Time Series Modeling
... This paper has conducted comparative studies of several representative methods for feature selection in the con- text of time series modeling. A modified correlation method is presented. In most of ...
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SARS Time Series Modeling and Spatial Data Analysis
... In this paper, we first create and analyze SARS spatial data, and use ArcGIS ArcMap 9.3 for data acquisition and collection of data stored in ArcCatalog create space database. Buffer and were analyzed using the network ...
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Time Series Modeling and Forecasting of CPI of Bangladesh
... with time series modeling and forecasting and published as “An Introductory Study on Time Series Modeling and ...advance time series modeling and forecasting ...
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Vector exponential time series modeling for polynomial J spectral factorization
... representation of an optimal controller for an H ∞ -problem associated with Σ and K of the symmetric canonical factor- ization of Φ(ζ, η). This fact opens a new avenue of approach to the solution of the kind of H ∞ ...
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Time Series Modeling of River Flow Using Wavelet Neural Networks
... modeled. Time series analysis requires mapping complex relationships between input(s) and output(s), since the forecasted values are mapped as a function of observed patterns in the ...the time ...
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Time Series Modeling for Trend Analysis and Forecasting Wheat Production of India
... advance. Time series forecasting is an important statistical technique used as a basis for manual and automatic planning in many application domains (Gooijer and Hyndman 2006; Sonawane et ...study, ...
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Autoregressive nonlinear time-series modeling of traffic fatalities in Europe
... The comparison of time series of road safety among different countries has been an interesting research topic. Lassarre [22] applies the local linear trend model to ten European countries and uses the ...
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Financial-Economic Time Series Modeling and Prediction Techniques – Review
... a time series into its linear and nonlinear components, have been shown to be successful for single models, but they show to have many ...linear modeling in order to identify and magnify the existing ...
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Time series modeling and forecasting of the consumer price index in Belgium
... As shown above, the mean is positive, i.e. 60.763. The minimum is 16 while the maximum is 113. The skewness is -0.023507 and the most striking characteristic is that it is positive, indicating that the B series is ...
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Advances in Statistical Network Modeling and Nonlinear Time Series Modeling
... with time-evolving edges, such as time-stamped social networks of interactions between peo- ple, and multi-layer networks, where edges are measured in multiple ways such as phone calls, text messages, ...
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Time series modeling and decomposition
... In another study, Dagum and Bianconcini (2008) derive two density functions and corresponding orthonormal polynomials to obtain two Reproducing Kernel Hilbert Space representations which give excellent results for ...
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Time series modeling for syndromic surveillance
... A number of different approaches have been developed for syndromic surveillance, with systems monitoring over the counter drug sales [11], web-based physician-entered reports [12], consumer health hotline telephone calls ...
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Modeling and trend analysis of leukemia in children using time series methods
... In this study, time series modeling was performed for blood cancer data over 2003- 2013. It was shown that the incidence of this cancer had increased until 2009 and then decreased. According to the ...
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Underwater Noise Modeling and Direction-Finding Based on Heteroscedastic Time Series
... and time-varying nature to the background ...in time series modeling of chang- ing variance or ...nonstationary time series such as financial ...
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Hybrid of ARIMA-GARCH modeling in rainfall time series
... rainfall series in Peninsular ...and time-variability of rainfall in Peninsular Malaysia and obtained an overview of rainfall ...rainfall series of three locations in peninsular Malaysia, observed ...
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A New High-order Takagi-Sugeno Fuzzy Model Based on Deformed Linear Models
... This particular selection of training and test data as well as x t and y t make our results comparable with other reported results [3]. The No Dimensional Error Index (NDEI), which is defined as the ratio of the root ...
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Prediction Mortality Rate Due to the Road-Traffic Accidents in Kazakhstan
... Determination coefficients of the obtained ap- proximations are quite significant. However, giv- en equations (second-degree polynomial) cannot be used in prediction of a phenomenon under review. This is due to the fact ...
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Time series analysis as input for clinical predictive modeling: Modeling cardiac arrest in a pediatric ICU
... As was the case for feature selection, an abundant number of strategies and algo- rithms can be employed to generate predictive models [99]. Again, at a very basic level, models can be divided into two groups: those that ...
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