NeuralNetwork Online Control to Road Tunnel with LongitudinalVentilation

An on-line controlmodel for road tunnelwith longitudinal ventilation was proposed based on neural networks and by combining traffic mode,l aerodynamics model and pollution mode.l Simulationwas conductedwith themode,l where the traffic volume changed from 1 000 to1 400 veh/h and the benchmark emission ratewas from 0. 008 to 0. 010m3/(veh·km). The results show that the proposed system increases or decreases the number of fans in realtime following the changes in the traffic volume and the benchmark emission rate, so that the volumetric fraction ofCO, as a control targe,t is controlled justunder the standard limit(150×10-6).