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Bai S.-H.,Nanjing University of Aeronautics and Astronautics | Bai S.-H.,National Key Laboratory of Airspace Technology
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | Year: 2010

Based on the conceptual framework and measurement method of system effectiveness developed via behavior analysis, this paper presents a layered model of objective tree and a contributory model characterized the behavior relationship between inner and outer elements of system. A set of computation formula is derived from the models which can be used to calculate the system effectiveness index and the system effectiveness factor. The contribution of inner and outer elements to the system effectiveness are discussed, which shows the reasonableness of the models and method. The methodology presented in this paper can be called contributory model method, or SEIF (System effectiveness index and factor) method, can be applied to the analysis and evaluation of system effectiveness. Source

Bai S.,Nanjing University of Aeronautics and Astronautics | Bai S.,National Key Laboratory of Airspace Technology | Lan H.,National Key Laboratory of Airspace Technology | Zheng N.,National Key Laboratory of Airspace Technology | And 2 more authors.
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | Year: 2011

The system effectiveness of an air traffic control (ATC) center and its variation directly affect the workload of a controller and the capacity of the airspace controlled by the ATC center. They are the key operational parameters of an ATC control system. Based on an effectiveness conceptual framework of system performance and the analytic method of a system contributory model, this article presents an effectiveness analysis procedure for the system of an ATC center. A 9×50 matrix is created which characterized the behavior of the whole system and the performance deviation caused by status changes of inner and outer elements. The value of each element contributing to the whole system is calculated upon an investigation of the opinions of system specialists and controllers. And the article performs an evaluation of the system effectiveness of an operational ATC center by this model, which reveals certain distinguishing features of system effectiveness and their variation. The evaluating results show good conformity with the judgment made by operation specialists, which verify the rationality of the effectiveness contributory model of an ATC system and the analytic approach used in this article. Source

Luo Y.-Q.,The Army 95899 of PLA | Luo Y.-Q.,National Key Laboratory of Airspace Technology | Chen Z.-J.,The Army 95899 of PLA | Chen Z.-J.,National Key Laboratory of Airspace Technology | And 4 more authors.
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | Year: 2015

To solve the problem that the flight delay is difficult to predict, the support vector machine regression method is used to establish the flight arrival delay prediction model. First, the phase space reconstruction theory is used to calculate the flight arrival delay's the delay time, embedded dimension and maximum Lyapunov exponent, and the chaotic characteristics of the flight arrival delay time sequence is found. The phase space of the flight arrival delay time sequence is reconstructed and combined with the departure delay of the upstream airport's flight using the same aircraft to build the input variable vector of the prediction model. Second, for selecting the optimal model parameters, the particle swarm algorithm, differential evolution algorithm and genetic algorithm are compared, the experiment shows that differential evolution algorithm can get the optimal prediction model with a higher probability. Last, the prediction performance of the model, the single factor prediction model and the relevance vector machine prediction model are compared. The results show that the prediction performance of the model is much better than the other two, the model can effectively predict flight delays. Copyright © 2015 by Science Press. Source

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