Application In Person-Job Evaluation Of BP Neural Network In Air Traffic Controller

Fight safety is the base of airline's survival and development. During the 'Eleventh Five-Year'period, China's civil aviation is going into a new round of rapid growth. At the same time, all industries in civil aviation, including air traffic control system, are under enormous pressure which is brought by rapid development of air transport industry and all of them are trying to strive to take measures to ensures to ensure air transport safety and normally. Recently, as air traffic accidents occurred without interruption, people have developed the point of worrying on air traffic safe. According to the statistics of'Flight Safety Foundation', there are a dozen global commercial aviation accidents until June in 2009 which is highest in recent ten years. Years of accident investigation showed that 3/4 of accidents are due to human causes. Air traffic controller is the change of the control system equipment. If they have a poor performance, there will been consequences of a state of chaos, fight-delays and other life-threatening. All above these will result into influence the efficiency of civil aviation. Therefore, researching in person-job fit in air traffic controller, is good to ATC system selection and provides a theoretical basis to optimize of the quality personnel.This article studies on person-job evaluation of BP Neural Network in air traffic. Through BP Neural Network computing, from the view of qualitative and quantitative to research on person-job evaluation in air traffic controller is its purpose. So around the post match, this paper focuses discussion from the following parts:Firstly, based on literature review, this paper had a research on the ATC branch in Hubei to understand the problems in person-job matching of air traffic controller, such as heavy work pressure, the body tired and lack of career planning and so on. This part is mainly to help the evaluation of person-job in air traffic control in next parts. Secondly, it focused on the design the evaluation indicator system of person-job fit in air traffic controller. After analyzing in-depth of the job description and job requirements, matching person-job fit theory, it constructed initially evaluation indicators system of person-job fit in air traffic controller, from the nature of knowledge, professional shills, general skills and physical and psychological quality. In order to ensure the scientific and applicability of indicator, we use Likert scale method, expert advice and recommendations by the questionnaires from air traffic sector of air traffic control system, to optimize the evaluation indicators, and selected 18 key indicators to build model and empirical study. Again, according to BP Neural Network, we constructed the evaluation model of person-job fit in air traffic controller. The point of this part is how to acquire the sample data. In this paper, the date from several experts of air traffic control in Hubei branch to make scores on each indicator. Finally, as the air traffic controller of Hubei air traffic control system branch an example, we established network parameters and training functions to validate BP Neural Network to match the measured position entirely feasible, and have a degree advantages in such problems.In this paper, based on BP Neural Network, we established evaluation model of person-job fit in traffic controller and had a sample calculation to the air traffic controller in Hubei branch of ATC. On the one hand, it overcomes the artificial in a comprehensive evaluation to determine the weight of the difficulties and the impact of randomness, and expanded the use of BP Neural Network field; on the other hand, it provides a theoretical basis for person-job fit evaluation model in air traffic control for ATC in China, and is good to select air traffic controllers, optimize the quality personnel of air traffic controllers, and conduct to the safety of civil aviation and operational efficiency.