There are currently nine permanent sensors deployed in several locations on some of the major highways in the area. From a modeling point of view the problem of dynamic traffic flow assignment can be viewed as the prediction of the behavior of traffic flow where the flow varies both temporally and spatially. After all the autocorrelations and cross-correlations between the 605 East bound and other sensors' have been calculated, the highest 6 correlation coefficients were used as input to the neural network. The 6 centers for each neuron were then calculated using K-means clustering algorithm. After the centers were computed, the width of each neuron was calculated and then we proceeded with the weight training via the least mean squared method.
Integration is the number of differences needed to take in a time-series to achieve stationarity.
The identification task is usually complex and time consuming. The training time took less than 5 minutes on a Pentium 100 computer. The number of vertices in the graph is n, and the number of edges is m. A label-setting method. A label-correcting method.