Airport Energy Optimization Scheduling Method Based On Data Mining Technology

The energy problem has become a major problem in the human development. The development of the global economy, increases the energy consumption. How to improve the efficiency of energy, has become the focus of the government and public concern. It is also the focus of the discussion research experts and scholars from all walks of life. Today, the civil aviation industry of china enters a rapid development period. The airport, as an air transport platform, provids lots of the resources such as water and electricity for passengers and airlines. In the airport, trying to reduce the consumption of energy has become the basic requirement of building a green airport and the implementation of energy-saving emission reduction.This research introduces the status of the existing energy optimization scheduling and the energy saving measures which taken by the airport. Then the main idea of this article is identified. With the data mining technology, the study finds the airport areas where energy consumption is unreasonable in the airport data, and optimizes the consumption of the energy.The main content of the article is as follows. The research designs a remote meter reading system which based on IBE scheme of data encryption. So, it can collect the electricity data of a airport completely. At the same time, it processes the airport data based on the wavelet analysis of the least square fitting algorithm. Then the study improved the traditional k-means algorithm for clustering mining. In order to get a clear relationship between the data, it finds the area where energy consumption is unreasonable with the mining of association rules which based on Apriori algorithm. Finally the research designs a scheduling scheme which based on the fuzzy control method and realizes the optimization scheduling of energy with the MATLAB simulation.