Earticle

초록

영어

In view of the problem A, first based on a large number of analysis reports and our own understandings, we defined "supply and demand matching degree" as β value can be quantified and obtained. And then by looking up the related document literature, through summary can get five groups of operational indicators easy to be obtained from the data as: population density, travel frequency, the selected proportion of the taxi, starting price, average waiting time, and the different areas and different time of target data represent different space-time concept in problem A. In the five groups of indicators data of Beijing time 8:00 to be correlation analysis with β, further selected four groups of strong correlation major indicators as population density, travel frequency, selected taxi ratio, average waiting time; then using selected these four groups of main indicators and β to build multivariate linear regression model, and the regression equation between β and every indicator is obtained; in order to verify the rationality of the established regression equation, with Beijing time 22:00 four groups of indicators into the model, get a set of β predictive value, and the actual value of the β using Pearson correlation coefficient to analyze the correlation, found the correlation is stronger, shows that the established model with strong degree of coincidence of the actual situation; so it can use this model to analyze the influence of different space and time indictor on the matching of supply and demand. In view of the problem B, it requires to design a reasonable and effective subsidy scheme, and verify the rationality of the scheme. An effective and reasonable subsidy scheme can inevitably reduce the problem of "difficult to take a taxi", by searching data, found that the taxi daily total mileage is a certain value, so the taxi daily effective mileage, can directly affect the difficulty level of taking a taxi. So we reflect the difficulty level of taking a taxi by the daily effective mileage of the taxi, and take it as a goal, combined with Module of Preventing Increase for the establishment of the model, through choosing the middle variables such as orders, software market shares, the frequency of taking a taxi, etc., to establish the relation function between daily mileage of the taxi with subsidies amount. It can be found from the observation function images, with the increase of the subsidies amount, the daily effective mileage of a taxi shows the tendency of increase first then decrease. Through consulting data, we can regulate the effective mileage above 250 kilometers can ease the difficulty of taking a taxi at the greatest extent. Then substitute it into the known data, compared with data obtained from function, the difference of both is not large, then it can be concluded that the scheme is reasonable.

목차

Abstract
 1. Problem restatement
 2. Model Hypothesis
 3. Problem Analysis
  3.1 Problem an Analysis
  3.2 Problem B Analysis
 4. Model Establishment and Solution
  4.1 Model Establishment and Solution of Problem A
  4.2 Model Establishment and Solution of Problem B
 5. Sensitivity Analysis
  5.1 Sensitivity Analysis of Problem A
  5.2 Sensitivity Analysis of Problem B
 6. Assessment and Promotion of the Model
  6.1 Model Advantages
  6.2 Model Disadvantages
  6.3 Model Improvement
  6.4. Model Promotion
 References

키워드

저자

• Xiaodong Xu [ North China Electric Power University, Baoding 071000, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Smart Home

• 간기

  격월간

• pISSN

  1975-4094

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605