In this article,we study the vector meson transitions among the charmonium and bottomonium states with the heavy quark effective theory in a systematic way,and make predictions for the ratios among the vector meson de...In this article,we study the vector meson transitions among the charmonium and bottomonium states with the heavy quark effective theory in a systematic way,and make predictions for the ratios among the vector meson decay widths of a special multiplet to another multiplet.The predictions can be confronted with the experimental data in the future.展开更多
A three-descriptor quantitative structure-property relationship （QSPR） model, based on the support vector machine （SVM） algorithm, was constructed to predict the glass transition temperatures （Tgs） ofpolyarylate...A three-descriptor quantitative structure-property relationship （QSPR） model, based on the support vector machine （SVM） algorithm, was constructed to predict the glass transition temperatures （Tgs） ofpolyarylates with complex structures. A total of 50 polyarylates were randomly divided into three sets, viz., the training set （30 polymers）, validation set （10 polymers） and prediction set （10 polymers）. By adjusting various parameters by trial and error, the final optimum SVM model based on Austin Model 1 （AM1） calculation is a polynomial kernel with the parameters C of 100, ε of 1.00E-05 and d of 2. The root-mean-square （RMS） errors obtained from the training set, validation set and prediction set are 19.4, 12.8 and 15.5 K, respectively. Research results show that the proposed SVM model has better statistical quality than the previous models. Thus, applying the SVM algorithm to predict Tgs of polymers is feasible.展开更多
基金Supported by National Natural Science Foundation of China under Grant No. 11075053the Fundamental Research Funds for the Central Universities
文摘In this article,we study the vector meson transitions among the charmonium and bottomonium states with the heavy quark effective theory in a systematic way,and make predictions for the ratios among the vector meson decay widths of a special multiplet to another multiplet.The predictions can be confronted with the experimental data in the future.
基金supported by the Open Project Program of Key Laboratory of Environmentally Friendly Chemistry and Applications of Ministry of Education,China (No.10HJYH06)
文摘A three-descriptor quantitative structure-property relationship （QSPR） model, based on the support vector machine （SVM） algorithm, was constructed to predict the glass transition temperatures （Tgs） ofpolyarylates with complex structures. A total of 50 polyarylates were randomly divided into three sets, viz., the training set （30 polymers）, validation set （10 polymers） and prediction set （10 polymers）. By adjusting various parameters by trial and error, the final optimum SVM model based on Austin Model 1 （AM1） calculation is a polynomial kernel with the parameters C of 100, ε of 1.00E-05 and d of 2. The root-mean-square （RMS） errors obtained from the training set, validation set and prediction set are 19.4, 12.8 and 15.5 K, respectively. Research results show that the proposed SVM model has better statistical quality than the previous models. Thus, applying the SVM algorithm to predict Tgs of polymers is feasible.
