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Regional wind power forecasting model with NWP grid data optimized
Zhao WANG, Weisheng WANG, Bo WANG
《能源前沿(英文)》 2017年 第11卷 第2期 页码 175-183 doi: 10.1007/s11708-017-0471-9
关键词: regional wind power forecasting feature set minimal-redundancy-maximal-relevance (mRMR) principal component analysis (PCA) locally weighted learning model
Peng WEI, Wenwen WANG, Yang YANG, Michael Yu WANG
《机械工程前沿(英文)》 2020年 第15卷 第3期 页码 390-405 doi: 10.1007/s11465-020-0588-0
关键词: level set method topology optimization density-based method level set band
吴小俊,杨静宇,王士同,刘同明,Josef Kittler
《中国工程科学》 2004年 第6卷 第2期 页码 44-47
对统计不相关最佳鉴别矢量集的本质进行研究,在基于总体散布矩阵特征分解的基础上,构造了一种白化变换,使得变换后的样本空间中的总体散布矩阵为单位矩阵,这样使得传统的最佳鉴别矢量集算法得到的均是具有统计不相关的最佳鉴别矢量集,从而揭示了统计不相关最佳鉴别变换的本质——白化变换加普通的线性鉴别变换。该方法的最大优点在于所获得的最优鉴别矢量同时具有正交性和统计不相关性。该方法对代数特征抽取具有普遍适用性。用ORL人脸数据库的数值实验,验证了该方法的有效性。
采用背景人声简化特征集的说话人识别直方图均衡化方法 Article
Myung-jae KIM, Il-ho YANG, Min-seok KIM, Ha-jin YU
《信息与电子工程前沿(英文)》 2017年 第18卷 第5期 页码 738-750 doi: 10.1631/FITEE.1500380
Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning
《机械工程前沿(英文)》 2021年 第16卷 第4期 页码 829-839 doi: 10.1007/s11465-021-0652-4
关键词: imbalanced fault diagnosis graph feature learning rotating machinery autoencoder
Maximum independent set in planning freight railway transportation
Gainanov Damir N., Mladenovic NENAD, Rasskazova V. A.
《工程管理前沿(英文)》 2018年 第5卷 第4期 页码 499-506 doi: 10.15302/J-FEM-2018031
This work is devoted to the problem of planning of freight railway transportation. We define a special conflict graph on the basis of a set of acceptable train routes. The investigation aims to solve the classical combinatorial optimization problem in relation to the maximum independent set of vertices in undirected graphs. The level representation of the graph and its tree are introduced. With use of these constructions, the lower and upper bounds for the number of vertices in the maximum independent set are obtained.
关键词: independent set algorithm planning of transportation two-sided estimate
Operating mechanism and set pair analysis model of a sustainable water resources system
Chaoyang DU,Jingjie YU,Huaping ZHONG,Dandan WANG
《环境科学与工程前沿(英文)》 2015年 第9卷 第2期 页码 288-297 doi: 10.1007/s11783-014-0642-4
关键词: sustainable water resources system operating mechanism set pair analysis model Shanghai
Dynamic simulation of gas turbines via feature similarity-based transfer learning
Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG
《能源前沿(英文)》 2020年 第14卷 第4期 页码 817-835 doi: 10.1007/s11708-020-0709-9
关键词: gas turbine dynamic simulation data-driven transfer learning feature similarity
《机械工程前沿(英文)》 2023年 第18卷 第2期 doi: 10.1007/s11465-022-0737-8
关键词: selective laser melting (SLM) build orientation determination multi-feature mechanical part (MFMP) fuzzy analytical hierarchy process multi-objective decision making (MODM)
徐勇,杨静宇,陆建峰
《中国工程科学》 2005年 第7卷 第10期 页码 38-42
在PCA基础上发展出的KPCA方法能抽取样本的非线性特征分量。然而, 基于KPCA的特征抽取需计算所有训练样本与待抽取特征的样本间的核函数, 因此, 训练集的大小制约着特征抽取的效率。为了提高效率,假设特征空间中变换轴可由一部分训练样本(节点)线性表出,并设计了改进的KPCA算法(IKPCA)。该算法抽取某样本特征时,只需计算该样本与节点间的核函数即可。实验结果显示,IKPCA在对应较好性能的同时,具有明显的效率上的优势。
XFEM schemes for level set based structural optimization
Li LI, Michael Yu WANG, Peng WEI
《机械工程前沿(英文)》 2012年 第7卷 第4期 页码 335-356 doi: 10.1007/s11465-012-0351-2
In this paper, some elegant extended finite element method (XFEM) schemes for level set method structural optimization are proposed. Firstly, two- dimension (2D) and three-dimension (3D) XFEM schemes with partition integral method are developed and numerical examples are employed to evaluate their accuracy, which indicate that an accurate analysis result can be obtained on the structural boundary. Furthermore, the methods for improving the computational accuracy and efficiency of XFEM are studied, which include the XFEM integral scheme without quadrature sub-cells and higher order element XFEM scheme. Numerical examples show that the XFEM scheme without quadrature sub-cells can yield similar accuracy of structural analysis while prominently reducing the time cost and that higher order XFEM elements can improve the computational accuracy of structural analysis in the boundary elements, but the time cost is increasing. Therefore, the balance of time cost between FE system scale and the order of element needs to be discussed. Finally, the reliability and advantages of the proposed XFEM schemes are illustrated with several 2D and 3D mean compliance minimization examples that are widely used in the recent literature of structural topology optimization. All numerical results demonstrate that the proposed XFEM is a promising structural analysis approach for structural optimization with the level set method.
关键词: structural optimization level set method extended finite element method (XFEM) computational accuracy and efficiency
Level set-based isogeometric topology optimization for maximizing fundamental eigenfrequency
Manman XU, Shuting WANG, Xianda XIE
《机械工程前沿(英文)》 2019年 第14卷 第2期 页码 222-234 doi: 10.1007/s11465-019-0534-1
关键词: topology optimization level set method isogeometric analysis eigenfrequency
Xingfan ZHOU,Zengling YANG,Longjian CHEN,Lujia HAN
《农业科学与工程前沿(英文)》 2016年 第3卷 第2期 页码 171-179 doi: 10.15302/J-FASE-2016095
关键词: self-organizing feature maps visualization processed animal proteins (PAPs) amino acid
《环境科学与工程前沿(英文)》 2022年 第16卷 第3期 doi: 10.1007/s11783-021-1471-x
• Hg bioaccumulation by phytoplankton varies among aquatic ecosystems.
关键词: Plankton Hg bioaccumulation Physiological characteristics A cross-system analysis Nutrient compositions Global data set
The research on structural damage identification using rough set and integrated neural network
Juelong LI, Hairui LI, Jianchun XING, Qiliang YANG
《机械工程前沿(英文)》 2013年 第8卷 第3期 页码 305-310 doi: 10.1007/s11465-013-0259-5
A huge amount of information and identification accuracy in large civil engineering structural damage identification has not been addressed yet. To efficiently solve this problem, a new damage identification method based on rough set and integrated neural network is first proposed. In brief, rough set was used to reduce attributes so as to decrease spatial dimensions of data and extract effective features. And then the reduced attributes will be put into the sub-neural network. The sub-neural network can give the preliminary diagnosis from different aspects of damage. The decision fusion network will give the final damage identification results. The identification examples show that this method can simplify the redundant information to reduce the neural network model, making full use of the range of information to effectively improve the accuracy of structural damage identification.
关键词: rough set integrated neural network damage identification decision making fusion
标题 作者 时间 类型 操作
Regional wind power forecasting model with NWP grid data optimized
Zhao WANG, Weisheng WANG, Bo WANG
期刊论文
Level set band method: A combination of density-based and level set methods for the topology optimization
Peng WEI, Wenwen WANG, Yang YANG, Michael Yu WANG
期刊论文
Imbalanced fault diagnosis of rotating machinery using autoencoder-based SuperGraph feature learning
期刊论文
Maximum independent set in planning freight railway transportation
Gainanov Damir N., Mladenovic NENAD, Rasskazova V. A.
期刊论文
Operating mechanism and set pair analysis model of a sustainable water resources system
Chaoyang DU,Jingjie YU,Huaping ZHONG,Dandan WANG
期刊论文
Dynamic simulation of gas turbines via feature similarity-based transfer learning
Dengji ZHOU, Jiarui HAO, Dawen HUANG, Xingyun JIA, Huisheng ZHANG
期刊论文
Build orientation determination of multi-feature mechanical parts in selective laser melting via multi-objective
期刊论文
Level set-based isogeometric topology optimization for maximizing fundamental eigenfrequency
Manman XU, Shuting WANG, Xianda XIE
期刊论文
composition differences between processed protein from different animal species by self-organizing feature
Xingfan ZHOU,Zengling YANG,Longjian CHEN,Lujia HAN
期刊论文
Characteristics of plankton Hg bioaccumulations based on a global data set and the implications for aquatic
期刊论文