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

机译:基于模糊控制器的混合智能交通流量预测新方法

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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:交通流量预测,这是防止高速公路拥堵的解决方案之一。由于交通流的行为方式不同,因此存在各种不同的条件,包括由于故障或传感器故障引起的数据丢失的可能性,不同的气候条件(如雨或雪)以及各种条件(如交通拥堵和事故发生)在旅途中,本文提出了一种新的预测模型。我们已经检查了在干扰中存在不同类型数据的情况下模型的鲁棒性。在MATLAB中基于真实数据进行了仿真,以显示该新模型的性能。

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