{"title":"Distinguishing chaos from random fractal sequences by the comparison of forward and backward predictions: utilization of the difference in time reversal symmetry of time series","authors":"M. Naito, N. Tanaka, H. Okamoto","doi":"10.1109/KES.1997.616863","DOIUrl":"https://doi.org/10.1109/KES.1997.616863","url":null,"abstract":"The authors propose a method for distinguishing chaos from random fractal sequences which have been difficult to discriminate from chaos. In the proposed method, the time series is predicted both in the forward direction and in the backward direction, and the accuracy of the two types of predictions is compared. They show, considering the time reversal symmetry of time series, that if the time series is chaotic and originates from a dissipative dynamical system, the accuracy is in general better for the forward prediction than for the backward prediction, whereas the accuracy is the same if the time series is a random fractal sequence. The method is also applicable to distinguishing between chaos and stationary noise. It is possible to give a quantitative evaluation of the distinction without a large amount of data or calculation.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"152 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":"134173862","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}
{"title":"Representations of game situations in fuzzy oriented GO system (FOG)","authors":"T. Yokogawa","doi":"10.1109/KES.1997.616859","DOIUrl":"https://doi.org/10.1109/KES.1997.616859","url":null,"abstract":"The paper presents a fuzzy oriented GO system, FOG, and its representations of game situations of GO in the open game. FOG has two basic components; an elementary GO system and a fuzzy organized engine. They communicate and compensate for each other. Representations of situations are by concepts expressed by language (GO terms) and strategic rules are given by the represented concepts. These rules can grasp macroscopic game situations in GO and compensate for reasoning based on game tree search and pattern oriented knowledge.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"14 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":"132071901","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}
{"title":"Selecting distinctive attributes for concept learning","authors":"A. Dengel, F. Dubiel","doi":"10.1109/KES.1997.616851","DOIUrl":"https://doi.org/10.1109/KES.1997.616851","url":null,"abstract":"This paper presents an innovative approach for learning the distinctive attributes of uncertain objects. The proposed system takes instances, clusters them into different concepts and consequently induces a hierarchy which is used for later classification. We introduce the major steps of the approach using a set of city attributes and further illustrate the applicability for a real world problem, namely the learning of structural concepts of business letters.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"3 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":"128469297","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}
{"title":"Robust matching in real-time 3D model-based tracking","authors":"Zheng Li, Han Wang","doi":"10.1109/KES.1997.616874","DOIUrl":"https://doi.org/10.1109/KES.1997.616874","url":null,"abstract":"In this paper, a new model-based tracking algorithm is proposed for real time performance. The matching process includes two aspects of: feature extraction using local minimum energy; and global matching of a known 3D model against the projected features. The algorithm is robust to change in lighting and backgrounds. The small motion hypothesis is used for fitting of feature energy which is defined as the negative absolute value of the edge strength. An autoregressive AR(1) model is employed for detecting incorrect matches in terms of the feature energy.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"37 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":"128729276","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}
{"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}
{"title":"Fuzzy developments of multichannel median filters","authors":"C. Vertan, C. Vertan, V. Buzuloiu","doi":"10.1109/KES.1997.619427","DOIUrl":"https://doi.org/10.1109/KES.1997.619427","url":null,"abstract":"The aim of the paper is to introduce two new multichannel median type filters, obtained by vector extension of their scalar (gray scale image) counterparts. The two filters are typical examples for two situations in image processing: the use of the fuzzy attribute to justify the weighting factors and the fuzzy attribute as descriptor for rule-based processing.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"94 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":"117039198","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}
{"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}
{"title":"A temporal neurofuzzy model for rule-based systems","authors":"F. Alpaslan, E. Bilen, L. Jain","doi":"10.1109/KES.1997.619454","DOIUrl":"https://doi.org/10.1109/KES.1997.619454","url":null,"abstract":"The paper reports the development of a temporal neuro-fuzzy model using fuzzy reasoning which is capable of representing the temporal information. The system is implemented as a feedforward multilayer neural network. The learning algorithm is a modification of the backpropagation algorithm. The system is aimed to be used in a medical diagnosis systems.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"36 1 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":"124256102","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}
{"title":"Fuzzy intelligent information processing in home appliances","authors":"N. Wakami, K. Mizutani, M. Kataoka, T. Imanaka","doi":"10.1109/KES.1997.616897","DOIUrl":"https://doi.org/10.1109/KES.1997.616897","url":null,"abstract":"We report an application of fuzzy logic to intelligent information processing. We have automated keyword extraction from a large amount of text information on teletext programs or Internet to provide users with a summary. With a part of this technique, we have also produced television sets which can summarize teletext news programs (in Japanese) into topics and display them for the users.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"38 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":"124978232","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}
{"title":"CT image reconstruction by back-propagation","authors":"Z. Nakao, F. Ali, Yenwei Chen","doi":"10.1109/KES.1997.619404","DOIUrl":"https://doi.org/10.1109/KES.1997.619404","url":null,"abstract":"A neural network model is used in CT image reconstruction from four projections. The system is based on the backpropagation algorithm for adaptation of connection weights. Satisfactory agreement between the original and reconstructed images was obtained in simulation, and the results obtained are compared to those obtained by the well-known algebraic reconstruction technique (ART), and it was found that the neural network method is more effective than ART when the number of projection directions is very limited.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"32 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":"131667338","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}