Research Article
Real-Time Travel Time Prediction Based on Evolving Fuzzy Participatory Learning Model
Algorithm 1
The algorithm of predicting travel time by ePL.
| (1) | Initialize the rule base; | | (2) | Read new data hk = [–1i]; | | (3) | Calculate link travel time ttk by (3); | | (4) | Make the input state vector and yk = [ttk ]; | | (5) | Use the input state vector xk to compute every compatibility index ρi and arousal index ai by (7) and (9); | | (6) | According to {…, ρi, …} and {…, ai, …}, update the rule center by (5) or create a new rule; | | (7) | Update the consequent parameters {…, γr, …} using GRLS in (16)–(20); | | (8) | Calculate each output yk i in rule base (1); | | (9) | Remove redundant rule according to the result of (10); | | (10) | Output the forecasting route travel time yk + 1 i. |
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