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This paper focuses on updating time varying demand matrices using real-time information. An Artificial Intelligence technique based on Distributed Evolutionary Algorithms (DEA), which is capable to exploit the use of grid computing, is developed. This EA-based demand estimation framework is implemented into a model that we call DynODE (Dynyamic O/D Estimator). DynODE provides a direct way of fusing...
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