Using molecular dynamics (MD) simulation, the diffusion of oxygen, methane, ammonia and carbon dioxide in water was simulated in the canonical NVT ensemble, and the diffusion coefficient was analyzed by the clustering...Using molecular dynamics (MD) simulation, the diffusion of oxygen, methane, ammonia and carbon dioxide in water was simulated in the canonical NVT ensemble, and the diffusion coefficient was analyzed by the clustering method. By comparing to the conventional method (using the Einstein model) and the differentiation-interval variation method, we found that the results ob- tained by the clustering method used in this study are more close to the experimental values. This method proved to be more reason- able than the other two methods.展开更多
Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the ...Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the length to width, stem girth, dates of budding, leaf yield and ratio of the prime-medium tobacco. The leaf number and the central leaf length showed a positive or a strong positive correlation with the yield per plant. And the leaf number and leaf yield per plant showed a strong positive correlation with the ratio of prime-medium tobacco. The results showed that the leaf yield per plant among these characteristics played a major role in determining the ratio of prime-medium tobacco while the others were less related with the ratio. Square sum of deviation method cluster analyses showed that 24 pure lines of flue-cured tobacco were clustered into two groups. Of the pure lines, Line T1706 and Line T1245 had a far relationship with all other lines, and also had a heterosis when crossed with the other lines. Lines Guangdonghuang 1 and R72（3）B-2-1 were closely related.展开更多
For the load modeling of a large power grid,the large number of substations covered by it must be segregated into several categories and,thereafter,a load model built for each type.To address the problem of skewed clu...For the load modeling of a large power grid,the large number of substations covered by it must be segregated into several categories and,thereafter,a load model built for each type.To address the problem of skewed clustering tree in the classical hierarchical clustering method used for categorizing substations,a fair hierarchical clustering method is proposed in this paper.First,the fairness index is defined based on the Gini coefficient.Thereafter,a hierarchical clustering method is proposed based on the fairness index.Finally,the clustering results are evaluated using the contour coefficient and the t-SNE two-dimensional plane map.The substations clustering example of a real large power grid considered in this paper illustrates that the proposed fair hierarchical clustering method can effectively address the problem of the skewed clustering tree with high accuracy.展开更多
By means of the series method, we obtain the exact analytical solution of clustering coefficient in random Apollonian networks [Phys. Rev. E 71 （2005）046141]. Our exact analytical result is identical with the simula...By means of the series method, we obtain the exact analytical solution of clustering coefficient in random Apollonian networks [Phys. Rev. E 71 （2005）046141]. Our exact analytical result is identical with the simulation, whereas in the original work, there is a deviation of about 4% between their approximate analytical result and the simulation.展开更多
The Joule-Thomson effect is one of the important thermodynamic properties in the system relevant to gas switching reforming with carbon capture and storage(CCS). In this work, a set of apparatus was set up to determin...The Joule-Thomson effect is one of the important thermodynamic properties in the system relevant to gas switching reforming with carbon capture and storage(CCS). In this work, a set of apparatus was set up to determine the Joule-Thomson effect of binary mixtures(CO_(2)+ H_(2)). The accuracy of the apparatus was verified by comparing with the experimental data of carbon dioxide. The Joule-Thomson coefficients(μ_(JT)) for(CO_(2)+ H_(2)) binary mixtures with mole fractions of carbon dioxide(x_(CO_(2))= 0.1, 0.26, 0.5,0.86, 0.94) along six isotherms at various pressures were measured. Five equations of state EOSs(PR,SRK, PR, BWR and GERG-2008 equation) were used to calculate the μ_(JT)for both pure systems and binary systems, among which the GERG-2008 predicted best with a wide range of pressure and temperature.Moreover, the Joule-Thomson inversion curves(JTIC) were calculated with five equations of state. A comparison was made between experimental data and predicted data for the inversion curve of CO_(2). The investigated EOSs show a similar prediction of the low-temperature branch of the JTIC for both pure and binary systems, except for the BWRS equation of state. Among all the equations, SRK has the most similar result to GERG-2008 for predicting JTIC.展开更多
In allusion to the disadvantage of having to obtain the number of clusters of data sets in advance and the sensitivity to selecting initial clustering centers in the k-means algorithm, an improved k-means clustering a...In allusion to the disadvantage of having to obtain the number of clusters of data sets in advance and the sensitivity to selecting initial clustering centers in the k-means algorithm, an improved k-means clustering algorithm is proposed. First, the concept of a silhouette coefficient is introduced, and the optimal clustering number Kopt of a data set with unknown class information is confirmed by calculating the silhouette coefficient of objects in clusters under different K values. Then the distribution of the data set is obtained through hierarchical clustering and the initial clustering-centers are confirmed. Finally, the clustering is completed by the traditional k-means clustering. By the theoretical analysis, it is proved that the improved k-means clustering algorithm has proper computational complexity. The experimental results of IRIS testing data set show that the algorithm can distinguish different clusters reasonably and recognize the outliers efficiently, and the entropy generated by the algorithm is lower.展开更多
文摘Using molecular dynamics (MD) simulation, the diffusion of oxygen, methane, ammonia and carbon dioxide in water was simulated in the canonical NVT ensemble, and the diffusion coefficient was analyzed by the clustering method. By comparing to the conventional method (using the Einstein model) and the differentiation-interval variation method, we found that the results ob- tained by the clustering method used in this study are more close to the experimental values. This method proved to be more reason- able than the other two methods.
基金Supported by Platform Construction for Germplasm Resources of China Tobacco (2007, 152)
文摘Correlation and path coefficient analyses were conducted for 10 characteristics of 24 pure lines of flue-cured tobacco such as plant height, knot distance, leaf number, the central leaf length and width, ratio of the length to width, stem girth, dates of budding, leaf yield and ratio of the prime-medium tobacco. The leaf number and the central leaf length showed a positive or a strong positive correlation with the yield per plant. And the leaf number and leaf yield per plant showed a strong positive correlation with the ratio of prime-medium tobacco. The results showed that the leaf yield per plant among these characteristics played a major role in determining the ratio of prime-medium tobacco while the others were less related with the ratio. Square sum of deviation method cluster analyses showed that 24 pure lines of flue-cured tobacco were clustered into two groups. Of the pure lines, Line T1706 and Line T1245 had a far relationship with all other lines, and also had a heterosis when crossed with the other lines. Lines Guangdonghuang 1 and R72（3）B-2-1 were closely related.
基金supported by the Major Science and Technology Project of Yunnan Province entitled“Research and Application of Key Technologies of Power Grid Operation Analysis and Protection Control for Improving Green Power Consumption”(202002AF080001)the China South Power Grid Science and Technology Project entitled“Research on Load Model and Modeling Method of Yunnan Power Grid”(YNKJXM20180017).
文摘For the load modeling of a large power grid,the large number of substations covered by it must be segregated into several categories and,thereafter,a load model built for each type.To address the problem of skewed clustering tree in the classical hierarchical clustering method used for categorizing substations,a fair hierarchical clustering method is proposed in this paper.First,the fairness index is defined based on the Gini coefficient.Thereafter,a hierarchical clustering method is proposed based on the fairness index.Finally,the clustering results are evaluated using the contour coefficient and the t-SNE two-dimensional plane map.The substations clustering example of a real large power grid considered in this paper illustrates that the proposed fair hierarchical clustering method can effectively address the problem of the skewed clustering tree with high accuracy.
基金Supported by the National Natural Science Foundation of China under Grant No 10675048the Research Foundation of Education Department of Hubei Province under Grant No Q20121512the Natural Science Foundation of Navy University of Engineering under Grant No 201200000033
文摘By means of the series method, we obtain the exact analytical solution of clustering coefficient in random Apollonian networks [Phys. Rev. E 71 （2005）046141]. Our exact analytical result is identical with the simulation, whereas in the original work, there is a deviation of about 4% between their approximate analytical result and the simulation.
基金supported by the National Natural Science Foundation of China (21878056)Key Laboratory of Petrochemical Resource Processing and Process Intensification Technology (2019Z002)。
文摘The Joule-Thomson effect is one of the important thermodynamic properties in the system relevant to gas switching reforming with carbon capture and storage(CCS). In this work, a set of apparatus was set up to determine the Joule-Thomson effect of binary mixtures(CO_(2)+ H_(2)). The accuracy of the apparatus was verified by comparing with the experimental data of carbon dioxide. The Joule-Thomson coefficients(μ_(JT)) for(CO_(2)+ H_(2)) binary mixtures with mole fractions of carbon dioxide(x_(CO_(2))= 0.1, 0.26, 0.5,0.86, 0.94) along six isotherms at various pressures were measured. Five equations of state EOSs(PR,SRK, PR, BWR and GERG-2008 equation) were used to calculate the μ_(JT)for both pure systems and binary systems, among which the GERG-2008 predicted best with a wide range of pressure and temperature.Moreover, the Joule-Thomson inversion curves(JTIC) were calculated with five equations of state. A comparison was made between experimental data and predicted data for the inversion curve of CO_(2). The investigated EOSs show a similar prediction of the low-temperature branch of the JTIC for both pure and binary systems, except for the BWRS equation of state. Among all the equations, SRK has the most similar result to GERG-2008 for predicting JTIC.
基金The National Natural Science Foundation of China(No50674086)Specialized Research Fund for the Doctoral Program of Higher Education (No20060290508)the Youth Scientific Research Foundation of China University of Mining and Technology (No2006A047)
文摘In allusion to the disadvantage of having to obtain the number of clusters of data sets in advance and the sensitivity to selecting initial clustering centers in the k-means algorithm, an improved k-means clustering algorithm is proposed. First, the concept of a silhouette coefficient is introduced, and the optimal clustering number Kopt of a data set with unknown class information is confirmed by calculating the silhouette coefficient of objects in clusters under different K values. Then the distribution of the data set is obtained through hierarchical clustering and the initial clustering-centers are confirmed. Finally, the clustering is completed by the traditional k-means clustering. By the theoretical analysis, it is proved that the improved k-means clustering algorithm has proper computational complexity. The experimental results of IRIS testing data set show that the algorithm can distinguish different clusters reasonably and recognize the outliers efficiently, and the entropy generated by the algorithm is lower.
