Bus Arrival Time Prediction Using Wavelet Neural Network Trained by Improved Particle Swarm Optimization

Table 2

Calibrated parameters of the IPSO-WNN model.

Weight	Calibrated parameters
	1	2	3	4	5	6	7	8	9	10
	0.428	−0.289	−0.675	−2.689	0.435	−0.025	−0.018	0.458	0.432	−0.074
	1.384	−0.291	0.732	−0.620	−0.583	0.506	−0.507	0.061	−0.376	0.294
	0.178	1.382	−1.342	0.987	−0.173	−0.085	0.366	0.230	1.007	0.405
	0.568	0.187	−0.206	0.351	−2.020	−0.140	0.084	−0.569	−0.900	−0.990
	−0.221	0.601	−0.023	−0.246	−0.021	−0.667	−0.291	−0.388	0.018	0.032
	0.076	−0.239	0.386	−0.126	−0.726	−0.058	−0.974	−0.079	0.664	0.405
	−0.689	−1.068	1.010	−0.458	0.229	1.663	−1.788	0.315	0.737	−0.468
	0.081	−0.208	0.470	−0.180	−1.030	−0.085	−0.789	−0.086	0.932	0.363
	0.547	0.292	−0.193	0.326	−1.800	−0.119	0.124	−0.589	−0.852	−1.135
	0.285	0.271	−0.034	−0.475	−1.131	0.154	−0.381	0.136	0.001	−0.988
aj	−1.602	−0.355	−0.694	0.223	−1.711	−0.004	−0.154	−1.092	−0.317	−0.832
bj	0.403	−0.219	0.767	−1.867	−1.509	−1.011	0.489	0.491	−1.466	1.427