A kind of combining forecasting model based on the generalized weighted functional mean is proposed. Two kinds of parameter estimation methods with its weighting coefficients using the algorithm of quadratic programmi...A kind of combining forecasting model based on the generalized weighted functional mean is proposed. Two kinds of parameter estimation methods with its weighting coefficients using the algorithm of quadratic programming are given. The efficiencies of this combining forecasting model and the comparison of the two kinds of parameter estimation methods are demonstrated with an example. A conclusion is obtained, which is useful for the correct application of the above methods.展开更多
Most edge-detection methods rely on calculating gradient derivatives of the potential field, a process that is easily affected by noise and is therefore of low stability. We propose a new edge-detection method named c...Most edge-detection methods rely on calculating gradient derivatives of the potential field, a process that is easily affected by noise and is therefore of low stability. We propose a new edge-detection method named correlation coefficient of multidirectional standard deviations（CCMS） that is solely based on statistics. First, we prove the reliability of the proposed method using a single model and then a combination of models. The proposed method is evaluated by comparing the results with those obtained by other edge-detection methods. The CCMS method offers outstanding recognition, retains the sharpness of details, and has low sensitivity to noise. We also applied the CCMS method to Bouguer anomaly data of a potash deposit in Laos. The applicability of the CCMS method is shown by comparing the inferred tectonic framework to that inferred from remote sensing（RS） data.展开更多
文摘A kind of combining forecasting model based on the generalized weighted functional mean is proposed. Two kinds of parameter estimation methods with its weighting coefficients using the algorithm of quadratic programming are given. The efficiencies of this combining forecasting model and the comparison of the two kinds of parameter estimation methods are demonstrated with an example. A conclusion is obtained, which is useful for the correct application of the above methods.
基金supported by the National Hi-Tech Research and Development Program of China(863 Program)(No.2006AA06Z107)the National Natural Science Foundation of China(No.40930314)
文摘Most edge-detection methods rely on calculating gradient derivatives of the potential field, a process that is easily affected by noise and is therefore of low stability. We propose a new edge-detection method named correlation coefficient of multidirectional standard deviations（CCMS） that is solely based on statistics. First, we prove the reliability of the proposed method using a single model and then a combination of models. The proposed method is evaluated by comparing the results with those obtained by other edge-detection methods. The CCMS method offers outstanding recognition, retains the sharpness of details, and has low sensitivity to noise. We also applied the CCMS method to Bouguer anomaly data of a potash deposit in Laos. The applicability of the CCMS method is shown by comparing the inferred tectonic framework to that inferred from remote sensing（RS） data.
