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Research Of Transport Capacity And Marketing Strategy Of DunHuang Railway

Posted on:2007-07-02Degree:MasterType:Thesis
Country:ChinaCandidate:H Y LuoFull Text:PDF
GTID:2189360215492366Subject:Transportation planning and management
Abstract/Summary:PDF Full Text Request
The predicting work of transport capacity and transport price level is essential and key job in project construction and even later operation. We can say that it is the beginning to do well in the forecasting of transport capacity and transport price level, and it is also the foundation of the construction scale and the economical appraisal to later operation. Meanwhile it is an important basis for the correct decision by the managers.The Artificial Neural Network (abbrevial as ANN) rising in recent years has abilities such as showing nonlinear relations and studying etc, and offers the new thoughts and methods to solve this kind of problems. The ANN researching method has very strong fault-tolerance quality and self-study ability, and is good at associating, summarizing, analogizing. It can be proved that the ANN may approximate all functions, which means that the ANN may automatically approximate those functions that best describe the data regularity of the samples whatever the forms the functions may have. So there will be good realistic meaning for later economic appraisal and judgment to apply the ANN to carry out the predicting of project research.Aimed at the disadvantages of the nowadays normal predicting methods in transport capacity, the method combining the ANN and the four-stage method is adopted according to the special condition of the line, and the forecasting model is built especially to the passenger capacity forecasting. The first step is to connect the GNP, average income, population and the passenger capacity of every OD region applying the ANN to prepare to carry out the forecasting , for the ANN can not only consider the influence of politics, economy and population, but also it can consider the influence of time, price and distance. The example showed that there are better convergence and perfect result when applying BP algorithm in the ANN model. In the second stage when calculating the traffic distribution, the Frator way is used to calculate the transport distribution of passenger capacity for the reason that Frator considers that the future transport capacity has relation with the increasing coefficient of the separate transport region and also the total increasing coefficient of each transport region. All the influences are taken into account. In the next stage, the induced passenger capacity is computed by gravity model method. The transferring part is calculated according to the sharing rate model which is contributed by transportation resistance, and the transport distribution adds the transferring part is the passenger demand. In the following content, the passenger density and its volume of circular flow of Liuyuan-Dunhuang segment are forecasted. Meanwhile the freight, its density and also the volume of circular flow are forecasted by the linear regression model. Combining the relative unit cost and volumes of circular flow, the transport price range is evaluated which will afford the support to the later economic budget. In the last chapter, those problems existing in the marketing management are analyzed and therefore the consideration how to settle them is provided. After the characteristic of this line is detailed analyzed, some strategies are put forward to supply reference to the management of its operation.
Keywords/Search Tags:BP neural networks, Four stages predicted methods, passenger forecasting, transport price, marketing strategy
PDF Full Text Request
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