The Research Of Decision Support System For Civil Aviation Energy Saving And Emission Reduction Based On Data Mining

Focus on the future development of civil aviation, the traditional three-dimensional model with "safety, efficiency, service" as its core is bound to change for the "safety,efficiency, service, environment" four-dimensional model, energy conservation and emission reduction of civil aviation has become one of the most forefront international issues of climate change. For the purpose of dealing with serious situation of the international air changing,reducing the emission according to China’s own goals, and insisting on three-step strategy civil aviation industry energy conservation, it is of great importance to carry out the forecasting work about energy conservation and emission reduction of civil aviation. Based on this, this paper focuses on researching into the measures of energy conservation and emission reduction of civil aviation, optimizes the measures whose rate of contribution is higher, and provides theoretical support for the research direction of key technologies.Firstly, the indexes used to measure the efficiency of energy conservation and emission reduction and its influencing factors are studied in-depth. Through analyzing and contrasting unit GDP energy consumption and carbon emission, the total energy consumption and carbon emission, energy consumption and carbon emissions per available tonne-kilometer and so on,according to the principles of ensuring the development, international standards and scientific reflection of the industry characteristics, energy consumption and carbon emissions per available tonne-kilometer is selected as the comprehensive index of measuring the efficiency of energy conservation and emission reduction. Through analyzing the selected comprehensive index, combined with the existing database and statistical reports, using the single-factor analyzing method, the main factors which will be studied are determined.Secondly, the tonne-kilometer fuel consumption model is built based on the data mining algorithm of data classification and regression analysis. Based on the existing database of an airline transport and production, first of all, make the data classification, so that each set of data has the great similarity and comparability. Select the group which has the large amount of data. Second, after the analysis and comparison of the fitting accuracy of different models,a quadratic polynomial regression model of tonne-kilometer fuel consumption is built, and using least square method to solve the specific expression of the model. Finally, it turns out that the model gets through the F-test, t test, goodness-of-fit test and the multi-collinearity test.Further more, standardize the parameter coefficient of the tonne-kilometer fuel consumption model, so that the contribution rates of the model parameters can be compared.Finally, the prototype decision support system of civil aviation energy saving and carbon emission is built. Through comparing the parameters’ contribution rates, combined with the functional requirements of the decision support system, the influence degree of the model parameters to the tonne-kilometer fuel consumption is compared, and the measures of energy saving and carbon emission which influence the tonne-kilometer fuel consumption is optimized.