检索范围:
排序: 展示方式:
Standard model of knowledge representation
Wensheng YIN
《机械工程前沿(英文)》 2016年 第11卷 第3期 页码 275-288 doi: 10.1007/s11465-016-0372-3
Knowledge representation is the core of artificial intelligence research. Knowledge representation methods include predicate logic, semantic network, computer programming language, database, mathematical model, graphics language, natural language, etc. To establish the intrinsic link between various knowledge representation methods, a unified knowledge representation model is necessary. According to ontology, system theory, and control theory, a standard model of knowledge representation that reflects the change of the objective world is proposed. The model is composed of input, processing, and output. This knowledge representation method is not a contradiction to the traditional knowledge representation method. It can express knowledge in terms of multivariate and multidimensional. It can also express process knowledge, and at the same time, it has a strong ability to solve problems. In addition, the standard model of knowledge representation provides a way to solve problems of non-precision and inconsistent knowledge.
关键词: knowledge representation standard model ontology system theory control theory multidimensional representation
Wang LIU, Jiabo ZHANG, Zhen HUANG, Dong HAN
《能源前沿(英文)》 2019年 第13卷 第2期 页码 367-376 doi: 10.1007/s11708-018-0584-9
关键词: ignition delay random sampling high dimensional model representation n-heptane fuel kinetics
Digital representation of meso-geomaterial spatial distribution and associated numerical analysis of
YUE Zhongqi
《结构与土木工程前沿(英文)》 2007年 第1卷 第1期 页码 80-93 doi: 10.1007/s11709-007-0008-0
关键词: homogeneous numerical analysis Expanded homogenization meso-level
李德毅
《中国工程科学》 2000年 第2卷 第10期 页码 73-79
知识表示一直是人工智能研究中的一个瓶颈,其难点在于知识中隐含有不确定性,即模糊性和随机性。文章提出用云模型3个数字特征(期望值,熵,超熵)来描述一个定性概念,用熵来关联模糊性和随机性。代表定性概念的云的某一次定量值,被称为云滴,可以用它对此概念的贡献度来衡量,许许多多云滴构成云,实现定性和定量之间的随时转换,反映了知识表示中的不确定性。论文以此对我国农历24个节气进行了新的量化解释。云方法已经用于数据开采、智能控制、跳频电台和大系统效能评估中,取得明显的效果。
A discussion of objective function representation methods in global optimization
Panos M. PARDALOS, Mahdi FATHI
《工程管理前沿(英文)》 2018年 第5卷 第4期 页码 515-523 doi: 10.15302/J-FEM-2018044
Non-convex optimization can be found in several smart manufacturing systems. This paper presents a short review on global optimization (GO) methods. We examine decomposition techniques and classify GO problems on the basis of objective function representation and decomposition techniques. We then explain Kolmogorov’s superposition and its application in GO. Finally, we conclude the paper by exploring the importance of objective function representation in integrated artificial intelligence, optimization, and decision support systems in smart manufacturing and Industry 4.0.
关键词: global optimization decomposition techniques multi-objective DC programming Kolmogorov’s superposition space-filling curve smart manufacturing and Industry 4.0
基于依存关系和多义词分析的句法词嵌入 None
Zhong-lin YE, Hai-xing ZHAO
《信息与电子工程前沿(英文)》 2018年 第19卷 第4期 页码 524-535 doi: 10.1631/FITEE.1601846
《能源前沿(英文)》 2023年 第17卷 第4期 页码 527-544 doi: 10.1007/s11708-023-0880-x
关键词: fault detection unary classification self-supervised representation learning multivariate nonlinear time series
Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang
《医学前沿(英文)》 2020年 第14卷 第4期 页码 488-497 doi: 10.1007/s11684-020-0762-0
关键词: knowledge representation uncertain causality graphical model artificial intelligence diagnosis dyspnea
Symbolic representation based on trend features for knowledge discovery in long time series
Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG
《信息与电子工程前沿(英文)》 2015年 第16卷 第9期 页码 744-758 doi: 10.1631/FITEE.1400376
关键词: Long time series Segmentation Trend features Symbolic Knowledge discovery
半监督堆叠距离自动编码器的表征学习在图像分类上的应用 Research Articles
侯亮,罗潇逸,汪子扬,梁军
《信息与电子工程前沿(英文)》 2020年 第21卷 第7期 页码 963-1118 doi: 10.1631/FITEE.1900116
邓敏,李成名,刘晓丽
《中国工程科学》 2013年 第15卷 第5期 页码 20-24
首先剖析了空间关系描述中“空间”的概念,论述了拓扑关系具有与实体位置本身无关的特性,进而阐述了空间实体的拓扑表达,分析了拓扑空间描述存在的不足,以及与地理环境、地理空间认知的相关性,提出了纳入度量特性的拓扑空间关系描述的方法。
The kinetic study of light alkene syntheses by CO 2 hydrogenation over Fe-Ni catalysts
Yaling ZHAO, Li WANG, Xiwei HAO, Jiazhou WU,
《化学科学与工程前沿(英文)》 2010年 第4卷 第2期 页码 153-162 doi: 10.1007/s11705-009-0241-2
关键词: representation corresponding orthogonal thermodynamic consistent
联邦无监督表示学习 Research Article
张凤达1,况琨1,陈隆1,游兆阳1,沈弢1,肖俊1,张寅1,吴超2,吴飞1,庄越挺1,李晓林3,4,5
《信息与电子工程前沿(英文)》 2023年 第24卷 第8期 页码 1181-1193 doi: 10.1631/FITEE.2200268
关键词: 联邦学习;无监督学习;表示学习;对比学习
Erratum to: Latent discriminative representation learning for speaker recognition Erratum
Duolin Huang, Qirong Mao, Zhongchen Ma, Zhishen Zheng, Sidheswar Routray, Elias-Nii-Noi Ocquaye,2211708034@stmail.ujs.edu.cn,mao_qr@ujs.edu.cn,zhongchen_ma@ujs.edu.cn,1209103822@qq.com,sidheswar69@gmail.com,eocquaye@ujs.edu.cn
《信息与电子工程前沿(英文)》 2021年 第22卷 第6期 页码 914-914 doi: 10.1631/FITEE.19e0690
标题 作者 时间 类型 操作
Applicability of high dimensional model representation correlations for ignition delay times of n-heptane
Wang LIU, Jiabo ZHANG, Zhen HUANG, Dong HAN
期刊论文
Digital representation of meso-geomaterial spatial distribution and associated numerical analysis of
YUE Zhongqi
期刊论文
A discussion of objective function representation methods in global optimization
Panos M. PARDALOS, Mahdi FATHI
期刊论文
Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and unary classification
期刊论文
Development of an artificial intelligence diagnostic model based on dynamic uncertain causality graph for the differential diagnosis of dyspnea
Yang Jiao, Zhan Zhang, Ting Zhang, Wen Shi, Yan Zhu, Jie Hu, Qin Zhang
期刊论文
Symbolic representation based on trend features for knowledge discovery in long time series
Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG
期刊论文
The kinetic study of light alkene syntheses by CO 2 hydrogenation over Fe-Ni catalysts
Yaling ZHAO, Li WANG, Xiwei HAO, Jiazhou WU,
期刊论文
Erratum to: Latent discriminative representation learning for speaker recognition
Duolin Huang, Qirong Mao, Zhongchen Ma, Zhishen Zheng, Sidheswar Routray, Elias-Nii-Noi Ocquaye,2211708034@stmail.ujs.edu.cn,mao_qr@ujs.edu.cn,zhongchen_ma@ujs.edu.cn,1209103822@qq.com,sidheswar69@gmail.com,eocquaye@ujs.edu.cn
期刊论文