A conflict is an event in which two or more aircraft experience a loss of minimum separation. In this paper, we formulate the problem of solving conflicts arising among several aircraft moving in a shared airspace as ...A conflict is an event in which two or more aircraft experience a loss of minimum separation. In this paper, we formulate the problem of solving conflicts arising among several aircraft moving in a shared airspace as a Constraint Satisfaction Problem (CSP). The constraint satisfaction problem being NP-complete, the algorithms developed to solve it have been of two types: non-systematic and systematic search methods. In this paper, we have considered a breakout algorithm as an example of non-systematic search methods and a backtracking procedure that maintains Arc Consistency (MAC) as an example of systematic search methods. The performance of these algorithms was compared experimentally and the Breakout algorithm is shown to be clearly superior.展开更多
A variational method based on previous numerical forecasts is developed to estimate and correct non-systematic component of numerical weather forecast error. In the method, it is assumed that the error is linearly dep...A variational method based on previous numerical forecasts is developed to estimate and correct non-systematic component of numerical weather forecast error. In the method, it is assumed that the error is linearly dependent on some combination of the forecast fields, and three types of forecast combination are applied to identifying the forecasting error: 1) the forecasts at the ending time, 2) the combination of initial fields and the forecasts at the ending time, and 3) the combination of the forecasts at the ending time and the tendency of the forecast. The Single Value Decomposition (SVD) of the covariance matrix between the forecast and forecasting error is used to obtain the inverse mapping from flow space to the error space during the training period. The background covariance matrix is hereby reduced to a simple diagonal matrix. The method is tested with a shallow-water equation model by introducing two different model errors. The results of error correction for 6, 24 and 48 h forecasts show that the method is effective for improving the quality of the forecast when the forecasting error obviously exceeds the analysis error and it is optimal when the third type of forecast combinations is applied.展开更多
文摘A conflict is an event in which two or more aircraft experience a loss of minimum separation. In this paper, we formulate the problem of solving conflicts arising among several aircraft moving in a shared airspace as a Constraint Satisfaction Problem (CSP). The constraint satisfaction problem being NP-complete, the algorithms developed to solve it have been of two types: non-systematic and systematic search methods. In this paper, we have considered a breakout algorithm as an example of non-systematic search methods and a backtracking procedure that maintains Arc Consistency (MAC) as an example of systematic search methods. The performance of these algorithms was compared experimentally and the Breakout algorithm is shown to be clearly superior.
基金Supported by National Natural Science Foundation of China (Grant Nos. 40875063 and 40505022)
文摘A variational method based on previous numerical forecasts is developed to estimate and correct non-systematic component of numerical weather forecast error. In the method, it is assumed that the error is linearly dependent on some combination of the forecast fields, and three types of forecast combination are applied to identifying the forecasting error: 1) the forecasts at the ending time, 2) the combination of initial fields and the forecasts at the ending time, and 3) the combination of the forecasts at the ending time and the tendency of the forecast. The Single Value Decomposition (SVD) of the covariance matrix between the forecast and forecasting error is used to obtain the inverse mapping from flow space to the error space during the training period. The background covariance matrix is hereby reduced to a simple diagonal matrix. The method is tested with a shallow-water equation model by introducing two different model errors. The results of error correction for 6, 24 and 48 h forecasts show that the method is effective for improving the quality of the forecast when the forecasting error obviously exceeds the analysis error and it is optimal when the third type of forecast combinations is applied.
