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A New Hybrid Intelligent Approach for Traffic Flow Forecasting based on Fuzzy Controllers

机译:基于模糊控制器的交通流预测新的混合智能方法

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Traffic flow forecasting, one of the solutions that prevent congestion on highways. Due to different behavioral patterns of traffic flow, a variety of different conditions, including the possibility of data loss due to a disturbance of failure or faulty sensors, different climatic conditions such as rain or snow, and various conditions such as traffic congestion and accident occurrence on the road, a new prediction model is presented in this paper. We have examined the robustness of the model in the presence of different types of data in a disturbance. Simulations based on real data were performed in MATLAB to show the performance of this new model.
机译:交通流预测,防止高速公路充血的解决方案之一。由于交通流量不同的行为模式,各种不同的条件,包括由于故障或故障传感器的干扰而导致数据丢失的可能性,诸如雨或雪等不同气候条件,以及交通拥堵和事故发生的各种条件在路上,本文提出了一种新的预测模型。我们已经在干扰存在不同类型的数据存在下检查了模型的稳健性。基于实际数据的模拟在Matlab中执行,以显示这种新模型的性能。

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