Purpose -The paper attempts to design an efficient algorithm for bearing track correlation of multi-sensor on the same platform using grey incidence analysis which is on the basis of the line segment Hausdorff distance. Design/methodology/approach -Starting from the line segment, Hausdorff distance that has been extended to calculate the distance between line segment sets by many scholars has been used for face recognition achieving good results. The degree of grey incidence is defined based on the above distance and properties which include normality, symmetry and closeness, are proved. Furthermore, a grey incidence matrix is built. With only the azimuth information detected by bearing sensors track correlation is difficult to judge, however grey incidence analysis can quickly and accurately determine whether two tracks are from the same target, and so an algorithm is designed to solve this dilemma. In the last part of the paper simulation experiment is conducted. Findings -The results are convincing: not only the algorithm proposed in the paper can solve the problem of track correlation of bearing-only sensors, but also the algorithm can judge the correlation degree of both tracks even in the case of intensive targets. Practical implications -The method exposed in the paper can be used to judge correlation degree of tracks detected by different sensors even for less information, and also be used to determine the similarity of two waveforms in the field of engineering. Originality/value -The paper succeeds in introducing the line segment Hausdorff distance into grey incidence analysis and on the basis of that an algorithm is designed to solve the problem of track correlation.
Purpose -The purpose of this paper is to attempt to analyze the situation and trend of China's energy consumption structure and predict it. Design/methodology/approach -Starting from the situation of China's energy consumption structure, a quadratic programming model is created to analyze the trend of it. A homogeneous Markov chain is chosen to predict China's energy consumption structure with the data collected from China's Statistical Yearbook. Finally, the implication of the prediction is explained. Findings -The results are convincing: the substitution of different energies are found, China will not enter the oil era, natural gas and non-fossil energy will rapidly develop. Practical implications -The results of this article can provide an important basis for the government to make a non-fossil energy development plan and energy policies. Originality/value -The paper succeeds in revealing and predicting China's energy consumption structure by quadratic programming and homogeneous Markov chain.
Purpose The purpose of this paper is to present a novel GREY‒ASMAA model for reliability growth evaluation in the large civil aircraft test flight phase. Design/methodology/approach As limited data are collected during the large civil aircraft test flight phase, which are not enough to meet the requirements of the ASMAA model for reliability growth, four basic GM(1, 1) models, even grey model, original difference grey model, even difference grey model and discrete grey model, are presented. Then both forward and backward grey models GM(1,1) are built to forecast and obtain virtual test data on left and right sides. Then the ASMAA model for reliability growth evaluation can be built based on original and virtual test data. Findings Aiming at the background of poor information data during the large civil aircraft test flight phase, first, a novel GREY‒ASMAA model, which was combined by the grey model GM(1,1) with the ASMAA model, has been put forward in this paper. Practical implications The GREY‒ASMAA model for reliability growth evaluation can be used to solve the problem of reliability growth evaluation with poor information data during the large civil aircraft test flight phase, and it has been used in reliability evaluation of C919 at the test flight stage. Originality/value This paper presents two new definitions of forward grey model GM(1,1) and backward grey model GM(1,1), as well as a novel GREY‒ASMAA model for reliability growth evaluation of large civil aircraft during test flight phase.
The allocation structure and expenditure structure of funds for science and technology in three executive bodies like colleges and universities, scientific research institutions and large and medium-sized enterprise in China are studied. The utilization efficiency of the funds for science and technology in every executive body are evaluated synthetically according to their output in scientific and technological activities. The problems existed in allocation and utilization of the funds for science and technology in China are pointed out. Based on these, some countermeasures and proposals for optimizing the allocation structure and increasing the utilization efficiency of the funds for science and technology in China are put forward.
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