This paper presents a hybrid approach to developing a short-term traffic flow prediction model. In this

approach a primary model is synthesized based on Neural Networks and then the model structure is optimized through

Genetic Algorithm. The proposed approach is applied to a rural highway, Ghazvin-Rasht Road in Iran. The obtained

results are acceptable and indicate that the proposed approach can improve model accuracy while reducing model

structure complexity. Minimum achieved prediction r2 is 0.73 and number of connection links at least reduced 20%

as a result of optimization.