Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1209-1214 |
| Number of pages | 6 |
| Journal | Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics |
| Volume | 32 |
| Issue number | 10 |
| State | Published - Oct 2006 |
Keywords
- Genetic algorithm
- Logistics volume of combined transportation
- Multi-objective prediction
- Neural network
- Structural equation model
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