As location-based techniques and applications have become ubiquitous in emerging wireless networks, the verification of location information has become more important. In recent years, there has been an explosion of a...As location-based techniques and applications have become ubiquitous in emerging wireless networks, the verification of location information has become more important. In recent years, there has been an explosion of activity related to lo- cation-verification techniques in wireless networks. In particular, there has been a specific focus on intelligent transport systems because of the mission-critical nature of vehicle location verification. In this paper, we review recent research on wireless location verification related to vehicular networks. We focus on location verification systems that rely on for- mal mathematical classification frameworks and show how many systems are either partially or fully encompassed by such frameworks.展开更多
This paper deals with the comparison of cyclone forecasts from the two versions of the operational global ensemble prediction system(EPS)at the National Centre for Medium Range Weather Forecasting(NEPS).The previous v...This paper deals with the comparison of cyclone forecasts from the two versions of the operational global ensemble prediction system(EPS)at the National Centre for Medium Range Weather Forecasting(NEPS).The previous version had a horizontal resolution of 33 km with 44 ensemble members(NEPS)whereas the updated version of this EPS has a resolution of 12 km with 11 members(NEPS-UP).The ensemble mean forecasts from both the models are compared using the direct position(DPE),along(ATE)and cross track(CTE)errors.For the verification of strike probability,Brier Score(BS),Brier Skill Score(BSS),Reliability Diagram,Relative Operating Characteristic(ROC)Curve and Root Mean Square Error(RMSE)in mean Vs Spread in members are used.For verification of intensity,RMSE in maximum wind speed from the ensemble mean forecasts are compared.Comparison of ensemble mean tracks from both models showed lower errors in NEPS-UP for all forecast lead times.The decrease in the DPE,ATE and CTE in NEPS-UP was around 38%,48%and 15%respectively.NEPS-UP showed lower BS and higher BSS values indicating a better match between observed frequencies and forecast probabilities as well as higher prediction skills.The reliability diagram showed higher accuracy for NEPS-UP as compared to NEPS.The ROC curves showed that for forecasts with higher probabilities the hit rate was high in NEPSUP.There was a greater consensus between the RMSE and Spread for NEPS-UP at all lead times.It was also seen that the RMSE in mean showed a 41%decrease from NEPS to NEPS-UP.On comparing maximum wind,it was found that for all lead times the RMSE in maximum wind speed for NEPS-UP was lower than NEPS.展开更多
基金supported by the University of New South Wales and the Australian Research Council under grant No.DP120102607
文摘As location-based techniques and applications have become ubiquitous in emerging wireless networks, the verification of location information has become more important. In recent years, there has been an explosion of activity related to lo- cation-verification techniques in wireless networks. In particular, there has been a specific focus on intelligent transport systems because of the mission-critical nature of vehicle location verification. In this paper, we review recent research on wireless location verification related to vehicular networks. We focus on location verification systems that rely on for- mal mathematical classification frameworks and show how many systems are either partially or fully encompassed by such frameworks.
文摘This paper deals with the comparison of cyclone forecasts from the two versions of the operational global ensemble prediction system(EPS)at the National Centre for Medium Range Weather Forecasting(NEPS).The previous version had a horizontal resolution of 33 km with 44 ensemble members(NEPS)whereas the updated version of this EPS has a resolution of 12 km with 11 members(NEPS-UP).The ensemble mean forecasts from both the models are compared using the direct position(DPE),along(ATE)and cross track(CTE)errors.For the verification of strike probability,Brier Score(BS),Brier Skill Score(BSS),Reliability Diagram,Relative Operating Characteristic(ROC)Curve and Root Mean Square Error(RMSE)in mean Vs Spread in members are used.For verification of intensity,RMSE in maximum wind speed from the ensemble mean forecasts are compared.Comparison of ensemble mean tracks from both models showed lower errors in NEPS-UP for all forecast lead times.The decrease in the DPE,ATE and CTE in NEPS-UP was around 38%,48%and 15%respectively.NEPS-UP showed lower BS and higher BSS values indicating a better match between observed frequencies and forecast probabilities as well as higher prediction skills.The reliability diagram showed higher accuracy for NEPS-UP as compared to NEPS.The ROC curves showed that for forecasts with higher probabilities the hit rate was high in NEPSUP.There was a greater consensus between the RMSE and Spread for NEPS-UP at all lead times.It was also seen that the RMSE in mean showed a 41%decrease from NEPS to NEPS-UP.On comparing maximum wind,it was found that for all lead times the RMSE in maximum wind speed for NEPS-UP was lower than NEPS.