According to the positive correlation of coal ash content and natural gamma, using a new coal core reposition method, which is ordered by global and local extreme, coal samples from medium-thickness seam are reasonabl...According to the positive correlation of coal ash content and natural gamma, using a new coal core reposition method, which is ordered by global and local extreme, coal samples from medium-thickness seam are reasonably located. Inte- grated the data of coal macrostructure characteristics, coal petrography analysis and coal gas production test, it studies the rela- tionship between coalbody structure and amplitude variation of different well logging data, and the tectonic coal recognition method with well logging data in fresh-water mud invasion. The results show that： the anomalous response of natural gamma ray, neutron, density and apparent resistivity does not reflect the coalbody structure type. In fresh-water drilling mud invasion, using the crossplot technique of dual-lateral, RXO resistivity response and the coalbody structure can classify granulated coal accurately; the proposed method is of good practicability and high reliability.展开更多
Aiming at the problem of the existing sorting for microstructure of fly ash, an improved scheme was put forward in this paper. First, fly ash particles are divided into four groups as low calcium, iron, high calcium a...Aiming at the problem of the existing sorting for microstructure of fly ash, an improved scheme was put forward in this paper. First, fly ash particles are divided into four groups as low calcium, iron, high calcium and char particle according to the substance components of fly ash. Then fly ash particles are divided into 14 sub groups, for example: cenospheres, plerospheres, solid spheres, porous char and dense char based on their chemical composition, shape and the characteristics of inner structure of fly ash. It has a distinct difference in granule configuration, inner structure and substance components. Some disadvantages of the existing scheme such as unilateralism and imprecision have been overcome in the advanced schemes.展开更多
In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary's discriminative power, the reconstruction error, classification error and inhomogeneous representat...In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary's discriminative power, the reconstruction error, classification error and inhomogeneous representation error are integrated into the objective function. The proposed approach learns a single structured dictionary and a linear classifier jointly. The learned dictionary encourages the samples from the same class to have similar sparse codes, and the samples from different classes to have dissimilar sparse codes. The solution to the objective function is achieved by employing a feature-sign search algorithm and Lagrange dual method. Experimental results on three public databases demonstrate that the proposed approach outperforms several recently proposed dictionary learning techniques for classification.展开更多
文摘According to the positive correlation of coal ash content and natural gamma, using a new coal core reposition method, which is ordered by global and local extreme, coal samples from medium-thickness seam are reasonably located. Inte- grated the data of coal macrostructure characteristics, coal petrography analysis and coal gas production test, it studies the rela- tionship between coalbody structure and amplitude variation of different well logging data, and the tectonic coal recognition method with well logging data in fresh-water mud invasion. The results show that： the anomalous response of natural gamma ray, neutron, density and apparent resistivity does not reflect the coalbody structure type. In fresh-water drilling mud invasion, using the crossplot technique of dual-lateral, RXO resistivity response and the coalbody structure can classify granulated coal accurately; the proposed method is of good practicability and high reliability.
文摘Aiming at the problem of the existing sorting for microstructure of fly ash, an improved scheme was put forward in this paper. First, fly ash particles are divided into four groups as low calcium, iron, high calcium and char particle according to the substance components of fly ash. Then fly ash particles are divided into 14 sub groups, for example: cenospheres, plerospheres, solid spheres, porous char and dense char based on their chemical composition, shape and the characteristics of inner structure of fly ash. It has a distinct difference in granule configuration, inner structure and substance components. Some disadvantages of the existing scheme such as unilateralism and imprecision have been overcome in the advanced schemes.
基金Supported by the National Natural Science Foundation of China(No.61379014)
文摘In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary's discriminative power, the reconstruction error, classification error and inhomogeneous representation error are integrated into the objective function. The proposed approach learns a single structured dictionary and a linear classifier jointly. The learned dictionary encourages the samples from the same class to have similar sparse codes, and the samples from different classes to have dissimilar sparse codes. The solution to the objective function is achieved by employing a feature-sign search algorithm and Lagrange dual method. Experimental results on three public databases demonstrate that the proposed approach outperforms several recently proposed dictionary learning techniques for classification.
