In recent years,wireless communication systems have experienced tremendous growth in data traffic.Many capacity-enhancing techniques are applied to elevate the gap between the amount of traffic and network capacity,and more solutions are required to minimize the gap.Traffic allocation among multiple networks is regarded as one of the most effective methods to solve the problem.However,current studies are unable to derive the quantity of traffic that each network should carry.An intelligent traffic allocation algorithm for multiple networks is proposed to obtain the optimal traffic distribution.Multiple factors affecting traffic distribution are considered in the proposed algorithm,such as network coverage,network cost,user habit,service types,network capacity and terminals.Using evaluations,we proved that the proposed algorithm enables a lower network cost than load balancing schemes.A case study of strategy making for a 2G system refarming is presented to further illustrate the applicability of the proposed algorithm.We demonstrated that the new algorithm could be applied in strategy making for telecommunication operators. In recent years, wireless communication systems have experienced tremendous growth in data traffic. Many capacity-enhancing techniques are applied to elevate the gap between the amount of traffic and network capacity, and more solutions are required to minimize the gap. Traffic allocation among multiple networks is considered as one of the most effective methods to solve the problem. However, current studies are unable to derive the quantity of traffic that each network should carry. An intelligent traffic allocation algorithm for multiple networks is proposed to obtain the optimal traffic distribution. Multiple factors affecting traffic distribution are considered in the proposed algorithm, such as network coverage, network cost, user habit, service types, network capacity and terminals.Using evaluations, we proved that the proposed algorithm enables a lower network cost than load balancing schemes .A case study of strategy making for a 2G system refarming is presented to further illustrate the applic ability of the proposed algorithm. We demonstrated that the new algorithm could be applied in strategy making for telecommunications operators.