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A novel method utilizing state space neural network (SSNN) with adaptive filters is proposed to estimate the traffic flow parameters. The SSNN's network topology is derived from delays and stops estimation problem, so the design of SSNN reflects the relationships that exist in physical traffic systems. To improve SSNN effectiveness, the adaptive filters is proposed to train the SSNN instead of conventional...
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