In real-life freeway transportation system, a few number of incident observation (very rare event) is available while there are large numbers of normal condition dataset. Most of researches on freeway incident detec...In real-life freeway transportation system, a few number of incident observation (very rare event) is available while there are large numbers of normal condition dataset. Most of researches on freeway incident detection have considered the incident detection problem as classification one. However, because of insufficiency of incident events, most of previous researches have utilized simulated incident events to develop freeway incident detection models. In order to overcome this drawback, this paper proposes a wavelet-based Hotelling 7a control chart for freeway incident detection, which integrates a wavelet transform into an abnormal detection method. Firstly, wavelet transform extracts useful features from noisy original traffic observations, leading to reduce the dimensionality of input vectors. Then, a Hotelling T2 control chart describes a decision boundary with only normal traffic observations with the selected features in the wavelet domain. Unlike the existing incident detection algorithms, which require lots of incident observations to construct incident detection models, the proposed approach can decide a decision boundary given only normal training observations. The proposed method is evaluated in comparison with California algorithm, Minnesota algorithm and conventional neural networks. The experimental results present that the proposed algorithm in this paper is a promising alternative for freeway automatic incident detections.展开更多
This paper proposes a multi-layer multi-agent model for the performance evaluation of powersystems,which is different from the existing multi-agent ones.To describe the impact of the structureof the networked power sy...This paper proposes a multi-layer multi-agent model for the performance evaluation of powersystems,which is different from the existing multi-agent ones.To describe the impact of the structureof the networked power system,the proposed model consists of three kinds of agents that form threelayers:control agents such as the generators and associated controllers,information agents to exchangethe information based on the wide area measurement system (WAMS) or transmit control signals tothe power system stabilizers (PSSs),and network-node agents such as the generation nodes and loadnodes connected with transmission lines.An optimal index is presented to evaluate the performance ofdamping controllers to the system's inter-area oscillation with respect to the information-layer topology.Then,the authors show that the inter-area information exchange is more powerful than the exchangewithin a given area to control the inter-area low frequency oscillation based on simulation analysis.展开更多
文摘In real-life freeway transportation system, a few number of incident observation (very rare event) is available while there are large numbers of normal condition dataset. Most of researches on freeway incident detection have considered the incident detection problem as classification one. However, because of insufficiency of incident events, most of previous researches have utilized simulated incident events to develop freeway incident detection models. In order to overcome this drawback, this paper proposes a wavelet-based Hotelling 7a control chart for freeway incident detection, which integrates a wavelet transform into an abnormal detection method. Firstly, wavelet transform extracts useful features from noisy original traffic observations, leading to reduce the dimensionality of input vectors. Then, a Hotelling T2 control chart describes a decision boundary with only normal traffic observations with the selected features in the wavelet domain. Unlike the existing incident detection algorithms, which require lots of incident observations to construct incident detection models, the proposed approach can decide a decision boundary given only normal training observations. The proposed method is evaluated in comparison with California algorithm, Minnesota algorithm and conventional neural networks. The experimental results present that the proposed algorithm in this paper is a promising alternative for freeway automatic incident detections.
基金supported in part by the National Natural Science Foundation of China under Grants Nos. 50707035, 50595411, 60425307, 60221301 and 50607005, in part by the 111 project (B08013)Program for Changjiang Scholars and Innovative Research Team in University (IRT0515)in part by the Program for New Century Excellent Talents in University (NCET-05-0216)
文摘This paper proposes a multi-layer multi-agent model for the performance evaluation of powersystems,which is different from the existing multi-agent ones.To describe the impact of the structureof the networked power system,the proposed model consists of three kinds of agents that form threelayers:control agents such as the generators and associated controllers,information agents to exchangethe information based on the wide area measurement system (WAMS) or transmit control signals tothe power system stabilizers (PSSs),and network-node agents such as the generation nodes and loadnodes connected with transmission lines.An optimal index is presented to evaluate the performance ofdamping controllers to the system's inter-area oscillation with respect to the information-layer topology.Then,the authors show that the inter-area information exchange is more powerful than the exchangewithin a given area to control the inter-area low frequency oscillation based on simulation analysis.