以Web of Science核心数据库中的已发表文献作为研究对象,运用Citespace软件的共现、共引聚类功能分析绘制二元性创新研究的知识图谱,探索了该领域的研究基础、前沿和热点。组织二元性、吸收能力、技术创新等作为该领域的研究热点备受关...以Web of Science核心数据库中的已发表文献作为研究对象,运用Citespace软件的共现、共引聚类功能分析绘制二元性创新研究的知识图谱,探索了该领域的研究基础、前沿和热点。组织二元性、吸收能力、技术创新等作为该领域的研究热点备受关注,而研究前沿主要集中在动态能力演变、组织架构、跨边界组织行为、新产品绩效等四个方面。展开更多
We improve the twin support vector machine(TWSVM)to be a novel nonparallel hyperplanes classifier,termed as ITSVM(improved twin support vector machine),for binary classification.By introducing the diferent Lagrangian ...We improve the twin support vector machine(TWSVM)to be a novel nonparallel hyperplanes classifier,termed as ITSVM(improved twin support vector machine),for binary classification.By introducing the diferent Lagrangian functions for the primal problems in the TWSVM,we get an improved dual formulation of TWSVM,then the resulted ITSVM algorithm overcomes the common drawbacks in the TWSVMs and inherits the essence of the standard SVMs.Firstly,ITSVM does not need to compute the large inverse matrices before training which is inevitable for the TWSVMs.Secondly,diferent from the TWSVMs,kernel trick can be applied directly to ITSVM for the nonlinear case,therefore nonlinear ITSVM is superior to nonlinear TWSVM theoretically.Thirdly,ITSVM can be solved efciently by the successive overrelaxation(SOR)technique or sequential minimization optimization(SMO)method,which makes it more suitable for large scale problems.We also prove that the standard SVM is the special case of ITSVM.Experimental results show the efciency of our method in both computation time and classification accuracy.展开更多
A binary decision diagram(BDD) is a data structure that is used to represent a Boolean function.Converting fault tree into BDD can effectively simplify counting processes and improve the accuracy and effectiveness of ...A binary decision diagram(BDD) is a data structure that is used to represent a Boolean function.Converting fault tree into BDD can effectively simplify counting processes and improve the accuracy and effectiveness of the results. However, due to various types of uncertainties in reliability data, we cannot obtain precise failure probabilities. In order to accurately quantify the certainties and obtain much more reliable results, we use BDD method based on fuzzy set theory for reliability quantitative analysis. In this regard, we take W-axis feeding system of heavy-duty computer numerical control(CNC) machine as a project example and adopt fuzzy BDD quantitative analysis method to analyze its reliability. The analysis results(aided by computer calculation)illustrate the effectiveness of the method proposed in this paper.展开更多
文摘以Web of Science核心数据库中的已发表文献作为研究对象,运用Citespace软件的共现、共引聚类功能分析绘制二元性创新研究的知识图谱,探索了该领域的研究基础、前沿和热点。组织二元性、吸收能力、技术创新等作为该领域的研究热点备受关注,而研究前沿主要集中在动态能力演变、组织架构、跨边界组织行为、新产品绩效等四个方面。
基金supported by National Natural Science Foundation of China(Grant Nos.11271361 and 70921061)the CAS/SAFEA International Partnership Program for Creative Research Teams,Major International(Regional)Joint Research Project(Grant No.71110107026)+1 种基金the Ministry of Water Resources Special Funds for Scientific Research on Public Causes(Grant No.201301094)Hong Kong Polytechnic University(Grant No.B-Q10D)
文摘We improve the twin support vector machine(TWSVM)to be a novel nonparallel hyperplanes classifier,termed as ITSVM(improved twin support vector machine),for binary classification.By introducing the diferent Lagrangian functions for the primal problems in the TWSVM,we get an improved dual formulation of TWSVM,then the resulted ITSVM algorithm overcomes the common drawbacks in the TWSVMs and inherits the essence of the standard SVMs.Firstly,ITSVM does not need to compute the large inverse matrices before training which is inevitable for the TWSVMs.Secondly,diferent from the TWSVMs,kernel trick can be applied directly to ITSVM for the nonlinear case,therefore nonlinear ITSVM is superior to nonlinear TWSVM theoretically.Thirdly,ITSVM can be solved efciently by the successive overrelaxation(SOR)technique or sequential minimization optimization(SMO)method,which makes it more suitable for large scale problems.We also prove that the standard SVM is the special case of ITSVM.Experimental results show the efciency of our method in both computation time and classification accuracy.
基金the National Natural Science Foundation of China(No.51405065)
文摘A binary decision diagram(BDD) is a data structure that is used to represent a Boolean function.Converting fault tree into BDD can effectively simplify counting processes and improve the accuracy and effectiveness of the results. However, due to various types of uncertainties in reliability data, we cannot obtain precise failure probabilities. In order to accurately quantify the certainties and obtain much more reliable results, we use BDD method based on fuzzy set theory for reliability quantitative analysis. In this regard, we take W-axis feeding system of heavy-duty computer numerical control(CNC) machine as a project example and adopt fuzzy BDD quantitative analysis method to analyze its reliability. The analysis results(aided by computer calculation)illustrate the effectiveness of the method proposed in this paper.
