Real-time crash prediction on freeways using data mining and emerging techniques

Recent advances in intelligent transportation system allow traffic safety studies to extend from historic data-based analyses to real-time applications. The study presents a new method to predict crash likelihood with traffic data collected by discrete loop detectors as well as the web-crawl weather data. Matched case-control method and support vector machines （SVMs） technique were employed to identify the risk status. The adaptive synthetic over-sampling technique was applied to solve the imbalanced dataset issues. Random forest technique was applied to select the contributing factors and avoid the over-fitting issues. The results indicate that the SVMs classifier could successfully classify 76.32% of the crashes on the test dataset and 87.52% of the crashes on the overall dataset, which were relatively satisfactory compared with the results of the previous studies. Compared with the SVMs classifier without the data, the SVMs classifier with the web-crawl weather data increased the crash prediction accuracy by 1.32% and decreased the false alarm rate by 1.72%, showing the potential value of the massive web weather data. Mean impact value method was employed to evaluate the variable effects, and the results are identical with the results of most of previous studies. The emerging technique based on the discrete traffic data and web weather data proves to be more applicable on real- time safety management on freeways.

Loop formation and stability of self-avoiding polymer chains

Using 3-dimensional Langevin dynamics simulations, we investigated the dynamics of loop formation of chains with excluded volume interactions, and the stability of the formed loop. The mean looping time ι1/scales with chain length N and corresponding scaling exponent α increases linearly with the capture radius scaled by the Kuhn length a/l due to the effect of finite chain length. We also showed that the probability density function of the looping time is well fitted by a single exponential. Finally, we found that the mean unlooping time ιu hardly depends on chain length N for a given a/l and that the stability of a formed loop is enhanced with increasing a/l.

An Intelligent Coordinated Protection and Control Strategy for Distribution Network with Wind Generation Integration

Integration of distributed generation(DG)can change the fault current level and direction in the distribution system,which affects the related protection system.In order to limit the negative impact of DG integration and upgrade the protection system performance,an intelligent coordinated protection and control strategy is proposed.A cost based optimization method is adopted to minimize the operation costs of possible solutions.Its aim is to define the optimal relay settings for the present operation condition,and the most suitable control mode of converter based wind turbine DG.Case studies on a hardware in the loop real time simulation platform demonstrate the proposed protection strategy.