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Speed Data (speed + data)
Kinds of Speed Data Selected AbstractsNear-Term Travel Speed Prediction Utilizing Hilbert,Huang TransformCOMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, Issue 8 2009Khaled Hamad In this study, we propose an innovative methodology for such prediction. Because of the inherently direct derivation of travel time from speed data, the study was limited to the use of speed only as a single predictor. The proposed method is a hybrid one that combines the use of the empirical mode decomposition (EMD) and a multilayer feedforward neural network with backpropagation. The EMD is the key part of the Hilbert,Huang transform, which is a newly developed method at NASA for the analysis of nonstationary, nonlinear time series. The rationale for using the EMD is that because of the highly nonlinear and nonstationary nature of link speed series, by decomposing the time series into its basic components, more accurate forecasts would be obtained. We demonstrated the effectiveness of the proposed method by applying it to real-life loop detector data obtained from I-66 in Fairfax, Virginia. The prediction performance of the proposed method was found to be superior to previous forecasting techniques. Rigorous testing of the distribution of prediction errors revealed that the model produced unbiased predictions of speeds. The superiority of the proposed model was also verified during peak periods, midday, and night. In general, the method was accurate, computationally efficient, easy to implement in a field environment, and applicable to forecasting other traffic parameters. [source] Time series analysis of wind speed with time-varying turbulenceENVIRONMETRICS, Issue 2 2006Bradley T. Ewing Abstract The characterization of the time series properties of wind speed, in terms of the mean and variance, is important and relevant to both engineers and businesses. This research investigates the first and second moments of the Texas Tech WERFL wind speed data utilizing the ARMA-GARCH-in-mean framework. The methodology allows the conditional variance to depend on the size of past shocks (i.e. gusts) in the series. Results have important implications for wind energy production as well as for the operational and financial hedging strategies of companies exposed to wind-related risk. The findings can be summarized as follows: (i) mean wind speeds measured at different heights above ground exhibit persistence and are highly dependent on immediate past wind speed values; (ii) regardless of the height at which the data were collected, wind speed exhibits time-varying variance; (iii) persistence in conditional variance increases with height at which the data were collected; (iv) there is strong evidence that conditional volatility is positively correlated with mean wind speed while the magnitude of this relationship declines with height. Copyright © 2005 John Wiley & Sons, Ltd. [source] Bootstrap simulations for evaluating the uncertainty associated with peaks-over-threshold estimates of extreme wind velocityENVIRONMETRICS, Issue 1 2003M. D. Pandey Abstract In the peaks-over-threshold (POT) method of extreme quantile estimation, the selection of a suitable threshold is critical to estimation accuracy. In practical applications, however, the threshold selection is not so obvious due to erratic variation of quantile estimates with minor changes in threshold. To address this issue, the article investigates the variation of quantile uncertainty (bias and variance) as a function of threshold using a semi-parametric bootstrap algorithm. Furthermore, the article compares the performance of L-moment and de Haan methods that are used for fitting the Pareto distribution to peak data. The analysis of simulated and actual U.S. wind speed data illustrates that the L-moment method can lead to almost unbiased quantile estimates for certain thresholds. A threshold corresponding to minimum standard error appears to provide reasonable estimates of wind speed extremes. It is concluded that the quantification of uncertainty associated with a quantile estimate is necessary for selecting a suitable threshold and estimating the design wind speed. For this purpose, semi-parametric bootstrap method has proved to be a simple, practical and effective tool. Copyright © 2003 John Wiley & Sons, Ltd. [source] A comparison of spatial interpolation methods to estimate continuous wind speed surfaces using irregularly distributed data from England and WalesINTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2008W. Luo Abstract Seven methods of spatial interpolation were compared to determine their suitability for estimating daily mean wind speed surfaces, from data recorded at nearly 190 locations across England and Wales. The eventual purpose of producing such surfaces is to help estimate the daily spread of pathogens causing crop diseases as they move across regions. The interpolation techniques included four deterministic and three geostatistical methods. Quantitative assessment of the continuous surfaces showed that there was a large difference between the accuracy of the seven interpolation methods and that the geostatistical methods were superior to deterministic methods. Further analyses, testing the reliability of the results, showed that measurement accuracy, density, distribution and spatial variability had a substantial influence on the accuracy of the interpolation methods. Independent wind speed data from ten other dates were used to confirm the robustness of the best interpolation methods. © Crown copyright 2007. Reproduced with the permission of Her Majesty's Stationery Office. Published by John Wiley & Sons, Ltd. [source] Determination of Weibull parameters for wind energy analysis of ,zmir, TurkeyINTERNATIONAL JOURNAL OF ENERGY RESEARCH, Issue 6 2002K. Ulgen Abstract In this study, the two Weibull parameters of the wind speed distribution function, the shape parameter k (dimensionless) and the scale parameter c (ms,1), were computed from the wind speed data for ,zmir. Wind data, consisting of hourly wind speed records over a 5-year period, 1995,1999, were measured in the Solar/Wind-Meteorological Station of the Solar Energy Institute at Ege University. Based on the experimental data, it was found that the numerical values of both Weibull parameters (k and c) for ,zmir vary over a wide range. The yearly values of k range from 1.378 to 1.634 with a mean value of 1.552, while those of c are in the range of 2.956,3.444 with a mean value of 3.222. The average seasonal Weibull distributions for ,zmir are also given. The wind speed distributions are represented by Weibull distribution and also by Rayleigh distribution, with a special case of the Weibull distribution for k=2. As a result, the Weibull distribution is found to be suitable to represent the actual probability of wind speed data for ,zmir (at annual average wind speeds up to 3 ms,1). Copyright © 2002 John Wiley & Sons, Ltd. [source] PHYSICAL, SENSORY AND FLOW PROPERTIES OF WHEAT STARCH,DAIRY BY-PRODUCT SPRAY-DRIED PEKMEZ MIXTURESJOURNAL OF TEXTURE STUDIES, Issue 2 2008DURMU ABSTRACT Pekmez, also known as a concentrated grape juice, was spray dried in a laboratory-type pilot drying unit to obtain pekmez powder (PP). The flow characteristics of PP, wheat starch (WS) and some dairy by-products (whey powder, skim milk powder, calcium caseinate and sodium caseinate) systems as binary and ternary mixtures were studied. The empirical power law model fitted the apparent viscosity,rotational speed data. PP,dairy by-product and WS,dairy by-product mixed solutions exhibited a shear-thinning behavior at 21C with flow behavior index (n) values of 0.86 , n , 0.92 and 0.06 , n , 0.27, respectively. WS,dairy by-product mixed solutions showed high shear-thinning behavior with the highest consistency index (k = 25,425,180,599 mPa·sn). However, PP,WS and PP,WS,dairy by-product mixed solutions at the same temperature exhibited the shear-thickening behavior with flow behavior index (n) values of 1.05 , n , 1.18. PRACTICAL APPLICATIONS Pekmez has become popular as a healthy food product; therefore, its rheologic properties were extensively studied by some researchers. However, pekmez powder (PP) is a new product and has not been produced yet in the food industry. Spray drying of foods has been spread recently in almost all food industry branches because it provides some advantages such as extending the shelf life, storage stability, decreasing the storage costs of the food products, etc. For this reason, production technology is first developed; PP is produced and studied in this study. There is no published data informing the rheologic, physical and sensory properties of pekmez or PP as binary and ternary mixtures with other components such as wheat starch (WS) and any dairy by-product. The purpose of this study was mainly to characterize the rheologic behavior of the PP,WS,dairy by-product mixed solutions and determine their physical and sensory properties. [source] Simulation and extremal analysis of hurricane eventsJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES C (APPLIED STATISTICS), Issue 3 2000E. Casson In regions affected by tropical storms the damage caused by hurricane winds can be catastrophic. Consequently, accurate estimates of hurricane activity in such regions are vital. Unfortunately, the severity of events means that wind speed data are scarce and unreliable, even by standards which are usual for extreme value analysis. In contrast, records of atmospheric pressures are more complete. This suggests a two-stage approach: the development of a model describing spatiotemporal patterns of wind field behaviour for hurricane events; then the simulation of such events, using meteorological climate models, to obtain a realization of associated wind speeds whose extremal characteristics are summarized. This is not a new idea, but we apply careful statistical modelling for each aspect of the model development and simulation, taking the Gulf and Atlantic coastlines of the USA as our study area. Moreover, we address for the first time the issue of spatial dependence in extremes of hurricane events, which we find to have substantial implications for regional risk assessments. [source] | |||||||||||||