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AUTOMATIC FREEWAY INCIDENT DETECTION SYSTEM USING ARTIFICIAL NEURAL NETWORKS AND GENETIC ALGORITHMS
AUTOMATIC FREEWAY INCIDENT DETECTION SYSTEM USING ARTIFICIAL NEURAL NETWORKS AND GENETIC ALGORITHMS
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机译：基于人工神经网络和遗传算法的高速公路自动事件检测系统
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摘要
Design of a neural network for automatic detection of incidents on a freeway is described. A neural network is trained usinga combination of both back-propagation and genetic algorithm-based methods for optimizing the design of the neural network. Theback-propagation and genetic algorithm work together in a collaborative manner in the neural network design. The training starts withincremental learning based on the instantaneous error and the global total error is accumulated for batch updating at the end of the trainingdata being presented to the neural network. The genetic algorithm directly evaluates the performance of multiple sets of neural networksin parallel and then use the analyzed results to breed new neural networks that tend to be better suited to the problems at hand.
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