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We propose incremental least squares density difference (LSDD) change detection method, an incremental test to detect changes in stationarity based on the difference between the unknown prechange and the post-change probability density functions (pdfs). The method is computationally light and, hence, adequate to process continuous datastreams, as those emerging from the Internet of Things and the...
The least squares density difference change detection test (LSDD-CDT) has proven to be an effective method in detecting concept drift by inspecting features derived from the discrepancy between two probability density functions (pdfs). The first pdf is associated with the concept drift free case, the second to the possible post change one. Interestingly, the method permits to control the ratio of...
We experience changes in stationarity/time variance in many practical applications. Since changes modify the operational framework the application is working with, its accuracy performance is in turn affected. When changes can occur, we need to detect them as soon as possible, in general by inspecting features extracted from data, and afterwards intervene to mitigate their effects. In this paper,...
Ramp metering has been developed as a traffic management strategy to alleviate congestion on freeways. Most ramp metering control algorithms are concerned without queuing consideration, because its still a tough job to deal with the problems of coordinated multiple ramps metering with queuing consideration. In this paper, on the basis of our previous studies, we use action-dependent heuristic dynamic...
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