Algorithm of multi-objective prediction on logistics volume of combined transportation

A new method was brought forward for the modeling of multi-objective prediction on logistics volume of combined transportation. Based on the standard of time, field, influence and combined transportation, using systems engineering antilogy, a model of four-dimensional factors of logistics volume was designed and optimized by using structural equation model. The fatal influencing factors of logistics volume of combined transportation were distilled. A new advanced neural network arithmetic integrated with genetic algorithm was put forward to make up the limitation of advanced neural network, and applied in a example of multi-objective prediction on logistics volume of combined transportation. Results show that this advanced algorithm performs steadily with high precision and convergence speed.