Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97最新文献_第4页

Expert system with an adaptive fuzzy inference module 带有自适应模糊推理模块的专家系统

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.619432

W. Kosinski, M. Weigl

{"title":"Expert system with an adaptive fuzzy inference module","authors":"W. Kosinski, M. Weigl","doi":"10.1109/KES.1997.619432","DOIUrl":"https://doi.org/10.1109/KES.1997.619432","url":null,"abstract":"An adaptive fuzzy expert system (AFES) is constructed as a hybrid in which an adaptive fuzzy inference module is combined with a neural network and equipped with a preprocessor of input data, user interface and a knowledge acquisition and modification unit. The adaptive fuzzy inference module (AFIM) is based on generalized Takagi-Sugeno fuzzy \"If-Then\" rules, forms of which have fuzzy sets involved only in premise parts, while consequent parts (i.e. the output of each rule) are functions of input variables. The final output of the module is the weighted sum of all the rule's output. The basic idea of AFIM is to realize a process of fuzzy reasoning and to express parameters of fuzzy reasoning by connection weights of a neural network and by forms of 4-parameter membership functions of fuzzy sets. The system is constructed for the needs of an opto-computer system for diagnosis of surface imperfections of technological elements. Similar systems can be useful in other situations, for example in the case of experimental results in which the data are imprecise and a unique functional relation between inputs and outputs is not reachable by means of classical methods.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127921108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Automatic generation of collision free moves for the ABB industrial robot control 自动生成无碰撞动作，适用于ABB工业机器人控制

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.619452

C. Blume

引用次数: 3

Selecting distinctive attributes for concept learning 选择独特的属性进行概念学习

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.616851

A. Dengel, F. Dubiel

引用次数: 0

Robust matching in real-time 3D model-based tracking 基于实时三维模型跟踪的鲁棒匹配

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.616874

Zheng Li, Han Wang

引用次数: 0

Acquiring and tuning knowledge representation parameters of fuzzy production rules using fuzzy expert networks 利用模糊专家网络获取和调优模糊产生规则的知识表示参数

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.619417

Eric C. C. Tsang, D. Yeung

{"title":"Acquiring and tuning knowledge representation parameters of fuzzy production rules using fuzzy expert networks","authors":"Eric C. C. Tsang, D. Yeung","doi":"10.1109/KES.1997.619417","DOIUrl":"https://doi.org/10.1109/KES.1997.619417","url":null,"abstract":"Fuzzy production rules (FPRs) have been used and proved to be a very useful knowledge representation method to capture and represent fuzzy, uncertain, incomplete and vague domain expert knowledge. The knowledge representation capability of these FPRs could be enhanced if parameters like local weights, certainty factors or threshold values are incorporated. These parameters, together with the membership values of fuzzy sets, are, however, difficult to acquire or extract from domain experts during the knowledge acquisition phases and to fine-tune during the system upgrade and maintenance phase. In this paper, the fuzzy expert networks (FENs) proposed by the authors in the World Congress on Neural Networks, pp. 500-3 (1996) are extended so that they can acquire and fine-tune more knowledge representation parameters (KRPs). Local weight is added to the KRPs and incorporated into the antecedent part of a conjunctive FPR. The knowledge acquisition and refinement problems of these parameters and the membership values of fuzzy sets can be solved by using FENs which not only have the reasoning mechanism of a fuzzy expert system (FES) but also the learning capability of a neural network. An experiment is presented to illustrate the workability of our proposed method.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116739496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Fuzzy developments of multichannel median filters 多通道中值滤波器的模糊发展

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.619427

C. Vertan, C. Vertan, V. Buzuloiu

引用次数: 2

Formal verification of the correctness in hybrid expert systems 混合专家系统正确性的形式化验证

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.619418

S. Shiu, J. Liu, D. Yeung

{"title":"Formal verification of the correctness in hybrid expert systems","authors":"S. Shiu, J. Liu, D. Yeung","doi":"10.1109/KES.1997.619418","DOIUrl":"https://doi.org/10.1109/KES.1997.619418","url":null,"abstract":"It has been increasingly recognized over recent years that expert systems which combine one or more techniques greatly increase the problem solving capability and help overcome some of the shortcomings associated with any single technique. The verification of these expert systems requires methods which could tackle the multiple knowledge representation paradigms and integrated inference mechanisms used. The paper provides a formal description technique for verifying the correctness of hybrid expert systems (HES) that emphasizes an integration of object hierarchy, property inheritance and production rules. The main idea is to convert the HES into a state controlled coloured Petri net (SCCPN) where the object hierarchy, property inheritance and production rules are modelled as separated components in the same SCCPN. The detection and analysis of the anomalies in the system are done by constructing and examining the reachability tree spanned by the knowledge inference. This provides a formal basis for automating the deduction process and a means of verifying HES. A set of propositions is formulated to verify errors and anomalies in HES. Lastly, future extension of the approach is discussed.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1997-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127043632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

A temporal neurofuzzy model for rule-based systems 基于规则系统的时间神经模糊模型

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.619454

F. Alpaslan, E. Bilen, L. Jain

引用次数: 1

Fuzzy intelligent information processing in home appliances 家电模糊智能信息处理

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.616897

N. Wakami, K. Mizutani, M. Kataoka, T. Imanaka

引用次数: 4

CT image reconstruction by back-propagation CT图像的反向传播重建

Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97 Pub Date : 1997-05-27 DOI: 10.1109/KES.1997.619404

Z. Nakao, F. Ali, Yenwei Chen

引用次数: 6