The causality diagram theory, which adopts graphical expression of knowledge and direct intensity of causality, overcomes some shortages in belief network and has evolved into a mixed causality diagram methodology for...The causality diagram theory, which adopts graphical expression of knowledge and direct intensity of causality, overcomes some shortages in belief network and has evolved into a mixed causality diagram methodology for discrete and continuous variable. But to give linkage intensity of causality diagram is difficult, particularly in many working conditions in which sampling data are limited or noisy. The classic learning algorithm is hard to be adopted. We used genetic algorithm to learn linkage intensity from limited data. The simulation results demonstrate that this algorithm is more suitable than the classic algorithm in the condition of sample shortage such as space shuttle’s fault diagnoisis.展开更多
A systematic approach for end-to-end QoS qualitative diagnosis and quantitative guarantee is proposed to support quality of service （QoS） management on current Internet. An automatic unwatched discretization algorit...A systematic approach for end-to-end QoS qualitative diagnosis and quantitative guarantee is proposed to support quality of service （QoS） management on current Internet. An automatic unwatched discretization algorithm for discretizing continuous numeric-values is brought forth to reshape these QoS metrics and contexts into their discrete forms. For QoS qualitative diagnosis, causal relationships between a QoS metric and its contexts are exploited with K2 Bayesian network （BN） structure learning by treating QoS metrics and contexts as BN nodes. A QoS metric node is qualitatively diagnosed to be causally related to its parent context nodes. To guarantee QoS quantitatively, those causal relationships are next modeled quantitatively by BN parameter learning. Then, BN inference can be carried out on the BN. Finally, the QoS metric is guaranteed to a specific value with certain probability by tuning its causal contexts to suitable values suggested by the BN inference. Our approach is validated to be sound and effective by simulations on a peer-to-peer （P2P） network.展开更多
Based on the empirical electronic theory of solids and molecules （EET）, the actual model for unit cell of cementite （0-FeaC） was built and the valence electron structures （VES） of cementite with specified site a...Based on the empirical electronic theory of solids and molecules （EET）, the actual model for unit cell of cementite （0-FeaC） was built and the valence electron structures （VES） of cementite with specified site and a number of Fe atoms substituted by alloying atoms of M （ M=Cr, V, W, Mo, Mn ） were computed by statistical method. By defining P as the stability factor, the stability of alloyed cementite with different numbers and sites of Fe atoms substituted by M was calculated. Calculation results show that the density of lattice electrons, the symmetry of distribution of covalent electron pairs and bond energy have huge influence on the stability of alloyed cementite. It is more stable as M substitutes for FeE than for Fe1. The alloyed cementite is the most stable when Cr, Mo, W and V substitute for 2 atoms of Fe2 at the sites of Nos. 2 and 3 （or No. 6 and No. 7）. The stability of alloyed cementite decreases gradually as being substitutional doped by W, Cr, V, Mo and Mn.展开更多
基金Funded by Chongqing High Tech Projects Foundation (No. 8277).
文摘The causality diagram theory, which adopts graphical expression of knowledge and direct intensity of causality, overcomes some shortages in belief network and has evolved into a mixed causality diagram methodology for discrete and continuous variable. But to give linkage intensity of causality diagram is difficult, particularly in many working conditions in which sampling data are limited or noisy. The classic learning algorithm is hard to be adopted. We used genetic algorithm to learn linkage intensity from limited data. The simulation results demonstrate that this algorithm is more suitable than the classic algorithm in the condition of sample shortage such as space shuttle’s fault diagnoisis.
基金Supported by the National High Technology Research and Development Program of China （No. 2007AA010302, 2009AA012404） the National Basic Research Program of China （No. 2007CB307103）+1 种基金 the National Natural Science Foundation of China （No. 60432010, 60802034） the Specialized Research Fund for the Doctoral Program of Higher Education （No. 20070013026）.
文摘A systematic approach for end-to-end QoS qualitative diagnosis and quantitative guarantee is proposed to support quality of service （QoS） management on current Internet. An automatic unwatched discretization algorithm for discretizing continuous numeric-values is brought forth to reshape these QoS metrics and contexts into their discrete forms. For QoS qualitative diagnosis, causal relationships between a QoS metric and its contexts are exploited with K2 Bayesian network （BN） structure learning by treating QoS metrics and contexts as BN nodes. A QoS metric node is qualitatively diagnosed to be causally related to its parent context nodes. To guarantee QoS quantitatively, those causal relationships are next modeled quantitatively by BN parameter learning. Then, BN inference can be carried out on the BN. Finally, the QoS metric is guaranteed to a specific value with certain probability by tuning its causal contexts to suitable values suggested by the BN inference. Our approach is validated to be sound and effective by simulations on a peer-to-peer （P2P） network.
基金Project(2014CFB801)supported by Natural Science Foundation of Hubei Province of ChinaProject(11304236)supported by the National Natural Science Foundation of China
文摘Based on the empirical electronic theory of solids and molecules （EET）, the actual model for unit cell of cementite （0-FeaC） was built and the valence electron structures （VES） of cementite with specified site and a number of Fe atoms substituted by alloying atoms of M （ M=Cr, V, W, Mo, Mn ） were computed by statistical method. By defining P as the stability factor, the stability of alloyed cementite with different numbers and sites of Fe atoms substituted by M was calculated. Calculation results show that the density of lattice electrons, the symmetry of distribution of covalent electron pairs and bond energy have huge influence on the stability of alloyed cementite. It is more stable as M substitutes for FeE than for Fe1. The alloyed cementite is the most stable when Cr, Mo, W and V substitute for 2 atoms of Fe2 at the sites of Nos. 2 and 3 （or No. 6 and No. 7）. The stability of alloyed cementite decreases gradually as being substitutional doped by W, Cr, V, Mo and Mn.
