Traffic Flow Anomaly Detection Based on Robust Ridge Regression with Particle Swarm Optimization Algorithm

Table 3

Optimization algorithm parameters.

Optimization algorithm	Parameter value
STA
GWO
GA
PSO

where represents the number of seeds of each optimization algorithm, the maxital represents the maximum number of the iterations of the optimization algorithms. For the STA: the value range of the rotation factor is , which decreases in the form of an exponential function with as the base with the increasing number of iterations; indicates the translation factor; indicates the expansion factor; indicates the axesion factor. For the GWO: is called the convergence factor and decreases from 2 linear to 0 with the increase of iterations; and are random numbers evenly distributed over an interval . For the GA: represents the mutation probability, and the Partial-Mapped crossover is used as the crossover operator. For the PSO algorithm: indicates the inertia factor; indicates the local learning factor; indicates the global learning factor; represents the maximum speed of the particle.