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Traffic signal control is an effective way to regulate traffic flow to avoid conflict and reduce congestion. The ACO (Ant Colony) algorithm is an optimization technique based on swarm intelligence. This research investigates the application of ACO to traffic signal control problem. The decentralized, collective, stochastic, and self-organization properties… (More)

- Sean O 'rourke, David Renfrew
- 2014

J o u r n a l o f P r o b a b i l i t y Electron. Abstract We study the asymptotic behavior of outliers in the spectrum of bounded rank perturbations of large random matrices. In particular, we consider perturbations of elliptic random matrices which generalize both Wigner random matrices and non-Hermitian random matrices with iid entries. As a consequence,… (More)

Using a generalized random recurrent neural network model, and by extending our recently developed mean-field approach [J. Aljadeff, M. Stern, and T. Sharpee, Phys. Rev. Lett. 114, 088101 (2015)], we study the relationship between the network connectivity structure and its low-dimensional dynamics. Each connection in the network is a random number with mean… (More)

— Traffic signal control is an effective way to improve the efficiency of traffic networks and reduce users' delays. Ant Colony Optimization (ACO) is a meta-heuristic algorithm based on the behavior of ant colonies searching for food. ACO has successfully been employed to solve many complicated combinatorial optimization problems and its stochastic and… (More)

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