Content extraction of HTML pages is the basis of the web page clustering and information retrieval,so it is necessary to eliminate cluttered information and very important to extract content of pages accurately.A nove...Content extraction of HTML pages is the basis of the web page clustering and information retrieval,so it is necessary to eliminate cluttered information and very important to extract content of pages accurately.A novel and accurate solution for extracting content of HTML pages was proposed.First of all,the HTML page is parsed into DOM object and the IDs of all leaf nodes are generated.Secondly,the score of each leaf node is calculated and the score is adjusted according to the relationship with neighbors.Finally,the information blocks are found according to the definition,and a universal classification algorithm is used to identify the content blocks.The experimental results show that the algorithm can extract content effectively and accurately,and the recall rate and precision are 96.5% and 93.8%,respectively.展开更多
Value relevance of accounting information analyses the relationship between accounting information and the mar—ket-value of equity.At present,the study of the value relevance gets into trouble:the correlation is not ...Value relevance of accounting information analyses the relationship between accounting information and the mar—ket-value of equity.At present,the study of the value relevance gets into trouble:the correlation is not high;a lot of findings are inconsistent.Through literature review,this paper analyses the logical origin and evolution of value relevance,points out that there are some flaws such as tacitly treeing capital market as semi-strong eficient,investors as rational an d their beliefs as homogeneous,pm—poses an approach to improve value relevan ce of accounting inform ation,and puts forward some advices for future study of value relevan ce of accounting information and policy-making.展开更多
针对具有多维状态变量、多种工作模式和故障模式的复杂工程系统,提出一种基于综合健康指数(synthesized health index,SHI)与相关向量机(relevance vector machine,RVM)的系统级失效预测方法。在离线训练阶段,先根据有限失效历史数据建...针对具有多维状态变量、多种工作模式和故障模式的复杂工程系统,提出一种基于综合健康指数(synthesized health index,SHI)与相关向量机(relevance vector machine,RVM)的系统级失效预测方法。在离线训练阶段,先根据有限失效历史数据建立各工作模式下的健康评估模型,并据此获得各历史退化轨迹的SHI序列;然后再使用RVM对这些序列进行回归处理,进而辨识出与回归曲线最为匹配的函数模型。在线预测阶段,先运用健康评估模型计算当前设备的SHI序列并进行RVM回归,再拟合出离线阶段确定的函数模型并添加时变噪声;最后,外推预测出系统剩余使用寿命的概率密度分布。该方法成功应用到涡轮发动机的失效预测案例。展开更多
A relevance vector machine (RVM) based fault diagnosis method was presented for non-linear circuits. In order to simplify RVM classifier, parameters selection based on particle swarm optimization (PSO) and preprocessi...A relevance vector machine (RVM) based fault diagnosis method was presented for non-linear circuits. In order to simplify RVM classifier, parameters selection based on particle swarm optimization (PSO) and preprocessing technique based on the kurtosis and entropy of signals were used. Firstly, sinusoidal inputs with different frequencies were applied to the circuit under test (CUT). Then, the resulting frequency responses were sampled to generate features. The frequency response was sampled to compute its kurtosis and entropy, which can show the information capacity of signal. By analyzing the output signals, the proposed method can detect and identify faulty components in circuits. The results indicate that the fault classes can be classified correctly for at least 99% of the test data in example circuit. And the proposed method can diagnose hard and soft faults.展开更多
A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for represent...A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action.The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory.Then,some chaotic invariants representing action can be captured in the reconstructed phase space.Finally,RVM was used to recognize action.Experiments were performed on the KTH,Weizmann and Ballet human action datasets to test and evaluate the proposed method.The experiment results show that the average recognition accuracy is over91.2%,which validates its effectiveness.展开更多
基金Project(2012BAH18B05) supported by the Supporting Program of Ministry of Science and Technology of China
文摘Content extraction of HTML pages is the basis of the web page clustering and information retrieval,so it is necessary to eliminate cluttered information and very important to extract content of pages accurately.A novel and accurate solution for extracting content of HTML pages was proposed.First of all,the HTML page is parsed into DOM object and the IDs of all leaf nodes are generated.Secondly,the score of each leaf node is calculated and the score is adjusted according to the relationship with neighbors.Finally,the information blocks are found according to the definition,and a universal classification algorithm is used to identify the content blocks.The experimental results show that the algorithm can extract content effectively and accurately,and the recall rate and precision are 96.5% and 93.8%,respectively.
文摘Value relevance of accounting information analyses the relationship between accounting information and the mar—ket-value of equity.At present,the study of the value relevance gets into trouble:the correlation is not high;a lot of findings are inconsistent.Through literature review,this paper analyses the logical origin and evolution of value relevance,points out that there are some flaws such as tacitly treeing capital market as semi-strong eficient,investors as rational an d their beliefs as homogeneous,pm—poses an approach to improve value relevan ce of accounting inform ation,and puts forward some advices for future study of value relevan ce of accounting information and policy-making.
文摘针对具有多维状态变量、多种工作模式和故障模式的复杂工程系统,提出一种基于综合健康指数(synthesized health index,SHI)与相关向量机(relevance vector machine,RVM)的系统级失效预测方法。在离线训练阶段,先根据有限失效历史数据建立各工作模式下的健康评估模型,并据此获得各历史退化轨迹的SHI序列;然后再使用RVM对这些序列进行回归处理,进而辨识出与回归曲线最为匹配的函数模型。在线预测阶段,先运用健康评估模型计算当前设备的SHI序列并进行RVM回归,再拟合出离线阶段确定的函数模型并添加时变噪声;最后,外推预测出系统剩余使用寿命的概率密度分布。该方法成功应用到涡轮发动机的失效预测案例。
基金Project(Z132012)supported by the Second Five Technology-based in Science and Industry Bureau of ChinaProject(YWF1103Q062)supported by the Fundemental Research Funds for the Central Universities in China
文摘A relevance vector machine (RVM) based fault diagnosis method was presented for non-linear circuits. In order to simplify RVM classifier, parameters selection based on particle swarm optimization (PSO) and preprocessing technique based on the kurtosis and entropy of signals were used. Firstly, sinusoidal inputs with different frequencies were applied to the circuit under test (CUT). Then, the resulting frequency responses were sampled to generate features. The frequency response was sampled to compute its kurtosis and entropy, which can show the information capacity of signal. By analyzing the output signals, the proposed method can detect and identify faulty components in circuits. The results indicate that the fault classes can be classified correctly for at least 99% of the test data in example circuit. And the proposed method can diagnose hard and soft faults.
基金Project(50808025) supported by the National Natural Science Foundation of ChinaProject(20090162110057) supported by the Doctoral Fund of Ministry of Education,China
文摘A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action.The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory.Then,some chaotic invariants representing action can be captured in the reconstructed phase space.Finally,RVM was used to recognize action.Experiments were performed on the KTH,Weizmann and Ballet human action datasets to test and evaluate the proposed method.The experiment results show that the average recognition accuracy is over91.2%,which validates its effectiveness.
