Quantifying Temporal and Spatial Correlation of Failure Events for Proactive Management

2007 ◽  
Author(s):  
Song Fu ◽  
Cheng-Zhong Xu
Keyword(s):  
Spatial Correlation ◽  
Proactive Management ◽  
Temporal And Spatial

scholarly journals Robust Energy Management in Active Distribution Systems Considering Temporal and Spatial Correlation

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 153635-153649 ◽  
Author(s):  
Suyang Zhou ◽  
Yi Zhao ◽  
Wei Gu ◽  
Zhi Wu ◽  
Yunpeng Li ◽  
...  
Keyword(s):  
Spatial Correlation ◽  
Energy Management ◽  
Distribution Systems ◽  
Temporal And Spatial

Probit-Based Time-Dependent Stochastic User Equilibrium Traffic Assignment Model

2008 ◽  
Vol 2085 (1) ◽  
pp. 86-94 ◽  
Author(s):  
Kuilin Zhang ◽  
Hani S. Mahmassani ◽  
Chung-Cheng Lu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Spatial Correlation ◽  
Traffic Assignment ◽  
User Equilibrium ◽  
The Other ◽  
Time Dependent ◽  
Stochastic User Equilibrium ◽  
Assignment Model ◽  
Temporal And Spatial

This study presents a time-dependent stochastic user equilibrium (TDSUE) traffic assignment model within a probit-based path choice decision framework that explicitly takes into account temporal and spatial correlation (traveler interactions) in travel disutilities across a set of paths. The TDSUE problem, which aims to find time-dependent SUE path flows, is formulated as a fixed-point problem and solved by a simulation-based method of successive averages algorithm. A mesoscopic traffic simulator is employed to determine (experienced) time-dependent travel disutilities. A time-dependent shortest-path algorithm is applied to generate new paths and augment a grand path set. Two vehicle-based implementation techniques are proposed and compared in order to show their impact on solution quality and computational efficiency. One uses the classical Monte Carlo simulation approach to explicitly compute path choice probabilities, and the other determines probabilities by sampling vehicles’ path travel costs from an assumed perception error distribution (also using a Monte Carlo simulation process). Moreover, two types of variance-covariance error structures are discussed: one considers temporal and spatial path choice correlation (due to path overlapping) in terms of aggregated path travel times, and the other uses experienced (or empirical) path travel times from a sample of individual vehicle trajectories. A set of numerical experiments are conducted to investigate the convergence pattern of the solution algorithms and to examine the impact of temporal and spatial correlation on path choice behavior.

scholarly journals Regional trend detection of Turkish river flows

2006 ◽  
Vol 37 (2) ◽  
pp. 165-182 ◽  
Author(s):  
Fatih Topaloğlu
Keyword(s):  
Spatial Correlation ◽  
Cross Correlation ◽  
Detection Technique ◽  
Trend Detection ◽  
Central Anatolia ◽  
Regional Trend ◽  
Parametric Test ◽  
Geographical Regions ◽  
Cross Correlations ◽  
Temporal And Spatial

This paper applies a procedure that identifies trends in hydrologic variables. The procedure utilizes the regional Mann–Kendall non-parametric test with and without both serial and cross-correlation to detect trends. The research investigates 15 streamflow variables including annual minimum, mean, maximum and monthly streamflows for a network of 75 streamflow gauging stations in seven geographical regions of Turkey. A considerable difference was obtained in the assessment of results with and without consideration of serial and cross correlation which might be due to a higher number of serial and cross-correlations among the sites in the geographical regions. Therefore, a quite different interpretation of these trend analyses would have been achieved if the temporal and spatial correlation of the streamflow series within the regions had been ignored. The application of the regional trend detection technique with both considerations has also resulted in the identification of significant decreasing trends in the Marmara, Aegean, Mediterranean and Central Anatolia regions. However, almost no evidence of significant change was observed with a general downward direction in the rest of the country. Besides, there are differences in the geographical regions of significant trends in the fifteen streamflow variables considered which implies that impacts on streamflows are not spatially uniform.

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