In order to solve the poor performance in text classification when using traditional formula of mutual information （MI） , a feature selection algorithm were proposed based on improved mutual information. The improve...In order to solve the poor performance in text classification when using traditional formula of mutual information （MI） , a feature selection algorithm were proposed based on improved mutual information. The improved mutual information algorithm, which is on the basis of traditional improved mutual information methods that enbance the MI value of negative characteristics and feature＇ s frequency, supports the concept of concentration degree and dispersion degree. In accordance with the concept of concentration degree and dispersion degree, formulas which embody concentration degree and dispersion degree were constructed and the improved mutual information was implemented based on these. In this paper, the feature selection algorithm was applied based on improved mutual information to a text classifier based on Biomimetic Pattern Recognition and it was compared with several other feature selection methods. The experimental results showed that the improved mutu- al information feature selection method greatly enhances the performance compared with traditional mutual information feature selection methods and the performance is better than that of information gain. Through the introduction of the concept of concentration degree and dispersion degree, the improved mutual information feature selection method greatly improves the performance of text classification system.展开更多
There are nearly 1 000 rice landrace varieties in the Taihu basin, China. To assess the genetic diversity of the rice, 24 intragenic molecular markers（representing 17 starch synthesis-related genes） were investigate...There are nearly 1 000 rice landrace varieties in the Taihu basin, China. To assess the genetic diversity of the rice, 24 intragenic molecular markers（representing 17 starch synthesis-related genes） were investigated in 115 Taihu basin rice landraces and 87 improved cultivars simultaneously. The results show that the average genetic diversity and polymorphism information content values of the landraces were higher than those of improved cultivars. In total, 41 and 39 allele combinations（of the 17 genes） were derived from the landraces and improved cultivars, respectively; only two identical allele combinations were found bet ween the two rice variety sources. Cluster analysis, based on the molecular markers, revealed that the rice varieties could be subdivided into five groups and, within these, the japonica improved rice and japonica landrace rice varieties were in two separate groups. According to the quality reference criteria to classify the rice into grades, some of the landraces were found to perform we ll, in terms of starch quality. For example, according to NY /T595-2002 criteria from the Ministry of Agriculture of China, 25 and 33 landraces reached grade 1, in terms of their apparent amylose content and gel consistency. Th e varieties that had outstanding quality could be used as breeding materials for rice quality breeding programs in the future. Our study is useful for future applications, such as genetic diversity studies, the protection of rice variety and improvment of rice quality in breeding programs.展开更多
To avoid the negative effects of disturbances on satellites,the characteristics of micro-vibration on flywheels are studied.Considering rotor imbalance,bearing imperfections and structural elasticity,the extended mode...To avoid the negative effects of disturbances on satellites,the characteristics of micro-vibration on flywheels are studied.Considering rotor imbalance,bearing imperfections and structural elasticity,the extended model of micro-vibration is established.In the feature extraction of micro-vibration,singular value decomposition combined with the improved Akaike Information Criterion(AIC-SVD)is applied to denoise.More robust and self-adaptable than the peak threshold denoising,AIC-SVD can effectively remove the noise components.Subsequently,the effective harmonic coefficients are extracted by the binning algorithm.The results show that the harmonic coefficients have great identification in frequency domain.Except for the fundamental frequency caused by rotor imbalance,the harmonics are also caused by the coupling of imperfections on bearing components.展开更多
基金Sponsored by the National Nature Science Foundation Projects (Grant No. 60773070,60736044)
文摘In order to solve the poor performance in text classification when using traditional formula of mutual information （MI） , a feature selection algorithm were proposed based on improved mutual information. The improved mutual information algorithm, which is on the basis of traditional improved mutual information methods that enbance the MI value of negative characteristics and feature＇ s frequency, supports the concept of concentration degree and dispersion degree. In accordance with the concept of concentration degree and dispersion degree, formulas which embody concentration degree and dispersion degree were constructed and the improved mutual information was implemented based on these. In this paper, the feature selection algorithm was applied based on improved mutual information to a text classifier based on Biomimetic Pattern Recognition and it was compared with several other feature selection methods. The experimental results showed that the improved mutu- al information feature selection method greatly enhances the performance compared with traditional mutual information feature selection methods and the performance is better than that of information gain. Through the introduction of the concept of concentration degree and dispersion degree, the improved mutual information feature selection method greatly improves the performance of text classification system.
基金financially supported by the National Natural Science Foundation of China(30800603)the Science and Technology Plan Projects of Taicang City,China(TC214YY3)the Building Program of the Science and Technology Innovation Team of Chien-Shiung Institute of Technology,China(2013CX02)
文摘There are nearly 1 000 rice landrace varieties in the Taihu basin, China. To assess the genetic diversity of the rice, 24 intragenic molecular markers（representing 17 starch synthesis-related genes） were investigated in 115 Taihu basin rice landraces and 87 improved cultivars simultaneously. The results show that the average genetic diversity and polymorphism information content values of the landraces were higher than those of improved cultivars. In total, 41 and 39 allele combinations（of the 17 genes） were derived from the landraces and improved cultivars, respectively; only two identical allele combinations were found bet ween the two rice variety sources. Cluster analysis, based on the molecular markers, revealed that the rice varieties could be subdivided into five groups and, within these, the japonica improved rice and japonica landrace rice varieties were in two separate groups. According to the quality reference criteria to classify the rice into grades, some of the landraces were found to perform we ll, in terms of starch quality. For example, according to NY /T595-2002 criteria from the Ministry of Agriculture of China, 25 and 33 landraces reached grade 1, in terms of their apparent amylose content and gel consistency. Th e varieties that had outstanding quality could be used as breeding materials for rice quality breeding programs in the future. Our study is useful for future applications, such as genetic diversity studies, the protection of rice variety and improvment of rice quality in breeding programs.
基金National Natural Science Foundation of China(No.U1831123)Fundamental Research Funds for the Central Universities,China(No.2232017A3-04)。
文摘To avoid the negative effects of disturbances on satellites,the characteristics of micro-vibration on flywheels are studied.Considering rotor imbalance,bearing imperfections and structural elasticity,the extended model of micro-vibration is established.In the feature extraction of micro-vibration,singular value decomposition combined with the improved Akaike Information Criterion(AIC-SVD)is applied to denoise.More robust and self-adaptable than the peak threshold denoising,AIC-SVD can effectively remove the noise components.Subsequently,the effective harmonic coefficients are extracted by the binning algorithm.The results show that the harmonic coefficients have great identification in frequency domain.Except for the fundamental frequency caused by rotor imbalance,the harmonics are also caused by the coupling of imperfections on bearing components.
