This paper gives a semantic fuzzy retrieval method of multimedia object, discusses the principle of fuzzy semantic retrieval technique, presents a fuzzy reasoning mechanism based on the knowledge base, and designs the...This paper gives a semantic fuzzy retrieval method of multimedia object, discusses the principle of fuzzy semantic retrieval technique, presents a fuzzy reasoning mechanism based on the knowledge base, and designs the relevant reasoning algorithms. Researchful results have innovative significance.展开更多
It is becoming an important social problem to make maintenance and rehabilitation of existing infrastructures such as bridges, buildings, etc. in the world. The kernel of such structure management is to develop a meth...It is becoming an important social problem to make maintenance and rehabilitation of existing infrastructures such as bridges, buildings, etc. in the world. The kernel of such structure management is to develop a method of safety assessment on items<span style="font-family:;" "=""> </span><span style="font-family:;" "="">which include remaining life and load carrying capacity. The purpose of this paper is to summarize the finding of up-to-date research articles concerning the application of knowledge-based systems to assessment and management of structures and to illustrate the potential of such systems in the structural engineering. In here, knowledge-based systems include knowledge-based expert systems incorporation with artificial neural networks, fuzzy reasoning and genetic or immune algorithms.</span><span style="font-family:;" "=""> </span><span style="font-family:;" "="">Specifically, two modern bridge management systems (BMS’s) are presented in the paper. The first is a BMS to assess the performance and derive optimal strategies for inspection and maintenance of concrete bridge structures using reliability based and knowledge-based systems. The second is the concrete bridge rating expert system (<i>J-BMS BREX</i>) to evaluate the performance of existing bridges by incorporating with artificial neural networks and fuzzy reasoning.</span>展开更多
When the classical constant false-alarm rate （CFAR） combined with fuzzy C-means （FCM） algorithm is applied to target detection in synthetic aperture radar （SAR） images with complex background, CFAR requires bloc...When the classical constant false-alarm rate （CFAR） combined with fuzzy C-means （FCM） algorithm is applied to target detection in synthetic aperture radar （SAR） images with complex background, CFAR requires block-by-block estimation of clutter models and FCM clustering converges to local optimum. To address these problems, this paper pro-poses a new detection algorithm： knowledge-based combined with improved genetic algorithm-fuzzy C-means （GA-FCM） algorithm. Firstly, the algorithm takes target region＇s maximum and average intensity, area, length of long axis and long-to-short axis ratio of the external ellipse as factors which influence the target appearing probabil- ity. The knowledge-based detection algorithm can produce preprocess results without the need of estimation of clutter models as CFAR does. Afterward the GA-FCM algorithm is improved to cluster pre-process results. It has advantages of incorporating global optimizing ability of GA and local optimizing ability of FCM, which will further eliminate false alarms and get better results. The effectiveness of the proposed technique is experimentally validated with real SAR images.展开更多
根据注塑知识的不确定性和诊断、优化的过程特点,对知识的具体表示和系统知识库的建立进行了深入的研究,采用符合CLIPS(C Language Integrated Production System)语言规范的产生式规则知识表示方式,建立了注塑制品缺陷分析专家系统的...根据注塑知识的不确定性和诊断、优化的过程特点,对知识的具体表示和系统知识库的建立进行了深入的研究,采用符合CLIPS(C Language Integrated Production System)语言规范的产生式规则知识表示方式,建立了注塑制品缺陷分析专家系统的知识库。并考虑到注塑制品缺陷知识具有模糊性和不确定性的特点,实现了用模糊知识表示方法和模糊推理技术完成注塑制品缺陷的诊断。展开更多
基于In ternet的计算机辅助工业设计系统,基于案例的计算机辅助工业设计系统研究基础上,结合Case-based Reason ing CBR技术,采用语义隶属度分析的方法,提出了基于设计问题的程序型知识获取模型以及基于相似度计算的程序型知识检索算法...基于In ternet的计算机辅助工业设计系统,基于案例的计算机辅助工业设计系统研究基础上,结合Case-based Reason ing CBR技术,采用语义隶属度分析的方法,提出了基于设计问题的程序型知识获取模型以及基于相似度计算的程序型知识检索算法,为计算机辅助工业设计提供了一个新的思维方式,并在CB ID系统构建中得到实践与验证。展开更多
文摘This paper gives a semantic fuzzy retrieval method of multimedia object, discusses the principle of fuzzy semantic retrieval technique, presents a fuzzy reasoning mechanism based on the knowledge base, and designs the relevant reasoning algorithms. Researchful results have innovative significance.
文摘It is becoming an important social problem to make maintenance and rehabilitation of existing infrastructures such as bridges, buildings, etc. in the world. The kernel of such structure management is to develop a method of safety assessment on items<span style="font-family:;" "=""> </span><span style="font-family:;" "="">which include remaining life and load carrying capacity. The purpose of this paper is to summarize the finding of up-to-date research articles concerning the application of knowledge-based systems to assessment and management of structures and to illustrate the potential of such systems in the structural engineering. In here, knowledge-based systems include knowledge-based expert systems incorporation with artificial neural networks, fuzzy reasoning and genetic or immune algorithms.</span><span style="font-family:;" "=""> </span><span style="font-family:;" "="">Specifically, two modern bridge management systems (BMS’s) are presented in the paper. The first is a BMS to assess the performance and derive optimal strategies for inspection and maintenance of concrete bridge structures using reliability based and knowledge-based systems. The second is the concrete bridge rating expert system (<i>J-BMS BREX</i>) to evaluate the performance of existing bridges by incorporating with artificial neural networks and fuzzy reasoning.</span>
基金supported by the National Natural Science Foundation of China(6107113961171122)+1 种基金the Fundamental Research Funds for the Central Universities"New Star in Blue Sky" Program Foundation the Foundation of ATR Key Lab
文摘When the classical constant false-alarm rate （CFAR） combined with fuzzy C-means （FCM） algorithm is applied to target detection in synthetic aperture radar （SAR） images with complex background, CFAR requires block-by-block estimation of clutter models and FCM clustering converges to local optimum. To address these problems, this paper pro-poses a new detection algorithm： knowledge-based combined with improved genetic algorithm-fuzzy C-means （GA-FCM） algorithm. Firstly, the algorithm takes target region＇s maximum and average intensity, area, length of long axis and long-to-short axis ratio of the external ellipse as factors which influence the target appearing probabil- ity. The knowledge-based detection algorithm can produce preprocess results without the need of estimation of clutter models as CFAR does. Afterward the GA-FCM algorithm is improved to cluster pre-process results. It has advantages of incorporating global optimizing ability of GA and local optimizing ability of FCM, which will further eliminate false alarms and get better results. The effectiveness of the proposed technique is experimentally validated with real SAR images.
文摘根据注塑知识的不确定性和诊断、优化的过程特点,对知识的具体表示和系统知识库的建立进行了深入的研究,采用符合CLIPS(C Language Integrated Production System)语言规范的产生式规则知识表示方式,建立了注塑制品缺陷分析专家系统的知识库。并考虑到注塑制品缺陷知识具有模糊性和不确定性的特点,实现了用模糊知识表示方法和模糊推理技术完成注塑制品缺陷的诊断。
