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- W2897763786 abstract "The paper presents an idea of developing a simple neural network based traffic controller using fuzzy inference rules. The design of a neural traffic control system is proposed. The proposed system efficiently handles the traffic flow and congestion in the intersection. The goal is achieved by managing the duration of green light interval. The neural traffic controller is able to calculate the green light time duration of traffic signal. The time duration is calculated based on the information regarding the number of cars on the two lanes where the signal is green i.e. Arrivals and the number of cars that are waiting on all the remaining lanes which have red signal i.e. Queue. The system will use fuzzy inference rule based strategy to train the neural network from the input data of Arrival and Queue and output data of Time for green light of signal. MATLAB simulations are used to present the validation of the test data results." @default.
- W2897763786 created "2018-10-26" @default.
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- W2897763786 date "2018-08-01" @default.
- W2897763786 modified "2023-09-25" @default.
- W2897763786 title "Fuzzy Inference Rule based Neural Traffic Light Controller" @default.
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- W2897763786 doi "https://doi.org/10.1109/icma.2018.8484382" @default.
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