Oil price pricing system of filling station

Abstract

The invention discloses an oil price pricing system of a filling station. The system comprises a server and a plurality of data acquisition terminals, the data acquisition terminals are respectively arranged at filling sites and used for acquiring monitoring data of the filling sites in a corresponding manner and sending the monitoring data to the server, the server comprises a model operation module, a database module and a data transmission module, the data transmission module receives the monitoring data transmitted through the data acquisition terminals and stores the monitoring data in the database module, the model operation module performs operation on the monitoring data and returns an operation result to the data acquisition terminals, and the model operation module comprises three operation programs including a conventional model, an unconventional model, and a gaming model. According to the system, the oil price is predicted through various algorithms of the conventional model, the unconventional model and the gaming model according to the monitoring data including competitor price, competition environment, road repair, site repair, and economic environment change acquired by the filling stations, and the recommendation prices of the filling site oil prices can be rapidly, accurately, and stably realized.

Description

technical field [0001] The invention relates to the technical field of oil price budgeting, in particular to an oil price pricing system for gas stations. Background technique [0002] Petroleum is the most widely used energy in the world today, and the study of oil price fluctuations is also one of the important aspects of the economy. There are many factors affecting oil prices, including both macro factors and micro factors that cannot be ignored, such as regional factors. Andrew Eckert (2011) tried to prove the factors affecting oil prices through traditional econometric analysis methods and linear regression. His conclusions mainly focused on macro factors, such as international oil prices and inflation. At the same time, it is also found that the relationship between some factors, such as oil demand and price, is constant in the short term and follows a fixed ratio. Matthias Firgo (2015) analyzed the impact of spatial distance on oil prices by establishing a spatial ...

AI Technical Summary

Problems solved by technology

The fifth is the efficiency problem when multiple sites jointly compete; that is, the problem of the lowest cost of internal competition or the minimization of losses

The disadvantages of this approach are: customer data collection is difficult; customer actions after price comparison are difficult to measure

The disadvantages of this method are: large amount of data collection and few authoritative data; high requirements for collection personnel

Therefore, the traditional pricing system is not fully suitable for the refined oil retail market at a time of change

Even the relatively mature method of determining oil prices at gas stations in the European and American markets still has problems in the current Chinese market: 1) Under the current competitive situation, the competition goal is usually "minimum loss" rather than quantity or efficiency. 2) Factors affecting the price of refined oil in China are changing rapidly at this stage; 3) Consumers and operators are immature, and there are many vicious price competitions and irrational consumption in the market; policies, The external environment such as roads changes frequently

[0010] It can be seen that the above-mentioned existing oil price forecasts still have the defects of inaccuracy, poor precision, and insufficient applicability, and further improvement is urgently needed

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