Study And Case Analysis On Forecast Of Regional Cargo

The logistics industry is an emerging indusry. It is considered to be connected with the world economy bridges, and to measure a country’s modernization level and the comprehensive national strength in21st Century. The logistics demand growth is rapid with the development of logistics industry in China. But there are malpractices in the process.Cargo is an important comparative indicator of logistics demand, cargo quantitative predictions for the logistics demand forecasting to provide a reliable basis for the planning of logistics systems and logistics infrastructure to provide a credible reference data. This paper described the basic meaning of regional logistics based on the combination of China’s regional logistics statistics status quo, and pointed out that the freight volume indicators reflect the logistics demand trends; In the analysis of the current commonly used prediction method the advantages and the disadvantages, according to the characteristics of regional cargo forecasting index, introducing the principal component analysis method, and the BP neural network and support vector machine artificial intelligent method for prediction of the combination, on the scale of logistics demand of Beijing City area was verified and forecast, put forward Beijing city over the next few years logistics planning advice.1. Described the basic connotation of a regional logistics and freight, the intrinsic relationship between the regional logistics and regional economy, cargo:Regional Logistics and regional economic interdependence continuum; Freight demand can be reflected to some extent, the variation of the logistics needs. Discusses the impact of the regional freight factors, and gives the principles and main steps of the regional cargo forecasts.2. Combination of regional logistics statistics status quo, that at this stage cargo indicators reflect changes in the logistics demand more practical significance, and gray theory to analyze the degree of correlation between the regional cargo and economic indicators, the results show that regional cargo and economic factorsbetween the existence of strong correlation.3. Analysis of advantages and disadvantages of the commonly used prediction method, according to the characteristics of regional cargo forecasting index, introducing the principal component analysis method, and from the regional cargo factors, was established based on BP neural network and support vector machine forecast model.4. In this paper, by using BP neural network and support vector machine artificial intelligent method for prediction of Beijing regional logistics demand forecasting, and achieved good results, the forecasting results show that:the introduction of the principal component analysis method, can improve the accuracy of prediction. Model extension application shows that, the next few years Beijing logistics demand upward trend, Beijing city policy system and safeguard measures to begin, ensure the healthy development of the logistics industry in Beijing city.