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Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium最新文献

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Decomposition of the brain portions by fuzzy inference techniques 用模糊推理技术分解大脑部分
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583586
N. Morinaga, Syoji Kobashi, N. Kamiura, Y. Hata, K. Yamato
{"title":"Decomposition of the brain portions by fuzzy inference techniques","authors":"N. Morinaga, Syoji Kobashi, N. Kamiura, Y. Hata, K. Yamato","doi":"10.1109/AFSS.1996.583586","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583586","url":null,"abstract":"The purpose of this paper establishes a method to decompose the brain region into the inherent portions. In it fuzzy inference is used to evaluate what portion each voxel belongs to. We develop a decomposition method based on standard region growing algorithm, which requires the inference results. The comparison of the volumes of our extracted portions with manually measured volumes by a medical doctor shows that on the average, the error rate is 2% for some MRI data.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"428 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116570015","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: 2
State dependent fuzzy controls by fuzzy singleton-type reasoning method 状态依赖模糊控制采用模糊单态推理方法
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583659
M. Mizumoto
{"title":"State dependent fuzzy controls by fuzzy singleton-type reasoning method","authors":"M. Mizumoto","doi":"10.1109/AFSS.1996.583659","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583659","url":null,"abstract":"This paper proposes a state dependent fuzzy reasoning method which is realized using fuzzy rule weights which vary with input values. The fuzzy singleton-type reasoning method is applied to fuzzy control in which fuzzy control rules are constrained with weights depending on input values, and good control results are obtained.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125752533","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: 13
A reinforcement learning control scheme for nonlinear systems with multiple actions 多动作非线性系统的强化学习控制方法
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583552
C. Chen, C. Jou
{"title":"A reinforcement learning control scheme for nonlinear systems with multiple actions","authors":"C. Chen, C. Jou","doi":"10.1109/AFSS.1996.583552","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583552","url":null,"abstract":"In this paper an attempt is made to apply reinforcement learning schemes to the adaptive control of nonlinear systems with multiple continuous control actions. The control task is formulated into a sequential optimization problem. A learning algorithm is developed based on the concepts of dynamic programming and stochastic approximation and the techniques of random search and parameter estimation. The proposed algorithm is complete and general enough so that the controller can be constituted by various computing models, e.g., neural networks. The efficiency of the proposed algorithm is demonstrated by applying the methods to the nonlinear control problems with multiple control actions.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127056678","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: 2
Fuzzy dialog analysis in reciprocal learning 互惠学习中的模糊对话分析
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583549
Shixiao Yang, T. Chan, J. Heh
{"title":"Fuzzy dialog analysis in reciprocal learning","authors":"Shixiao Yang, T. Chan, J. Heh","doi":"10.1109/AFSS.1996.583549","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583549","url":null,"abstract":"The dialog behavior between two learning companions in RTS (Reciprocal Tutoring System) is analyzed through fuzzy set theory. RTS is a collaborative learning system with two learning companions playing two roles: tutor and tutee. By communication, these two learners share their ideas and solve programming exercises cooperatively. Each linguistic sentence of their talks belongs to a fuzzy set that indicates different kinds of dialog style. Through processing the experimental data, the fuzzy dialog vectors of different styles can be calculated and all the fuzzy transition relations can also be estimated to find out all kinds of dialog path. As results, students use different dialog styles to express their intention, instead of just using one dialog mode and tutee likes to ask tutor \"Why\" to make tutor find some correct key point. All these results can also be useful in studying student model and implementing a good virtual learning companion.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"353 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132382474","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
3D automatic extraction method of the brain regions aided by fuzzy matching techniques 基于模糊匹配技术的脑区三维自动提取方法
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583585
Syoji Kobashi, N. Kamiura, Y. Hata, K. Yamato
{"title":"3D automatic extraction method of the brain regions aided by fuzzy matching techniques","authors":"Syoji Kobashi, N. Kamiura, Y. Hata, K. Yamato","doi":"10.1109/AFSS.1996.583585","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583585","url":null,"abstract":"In the field of medical science, the extraction of the brain regions from MR images is valuable to diagnose an Alzheimer's disease. We propose here a novel approach to extract the brain region using the fuzzy matching technique. We describe a modeling of the intensity histogram by fuzzy logic and evaluate fuzzy matching techniques for the extraction of the brain region. We develop the extraction algorithm based on a standard region growing technique. An experimental result on 36 MRI data shows that the error rate is 2.4%, on the average, against manually extracted volumes by a medical doctor.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122201506","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: 9
A fuzzy-logic based trade-off analysis for aggregating flexibility measures of FMSs 基于模糊逻辑的FMSs柔性度量综合权衡分析
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583690
H. Kao, Yunfen Hou, J. Lee, J. Kuo
{"title":"A fuzzy-logic based trade-off analysis for aggregating flexibility measures of FMSs","authors":"H. Kao, Yunfen Hou, J. Lee, J. Kuo","doi":"10.1109/AFSS.1996.583690","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583690","url":null,"abstract":"Manufacturing flexibility is a complex and multidimensional concept which lacks a universally accepted set of measures and remains a sought after attribute of flexible manufacturing systems (FMSs). Instead of focusing on the measurement of key characteristics of system flexibility, the paper applies a fuzzy logic based technique to identify the trade-off relationships among flexibility measures and establish an aggregation hierarchy for ranking alternative FMS systems.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115318008","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: 0
Application of fuzzy multisets to fuzzy database systems 模糊多集在模糊数据库系统中的应用
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583573
K.-S. Kim, S. Miyamoto
{"title":"Application of fuzzy multisets to fuzzy database systems","authors":"K.-S. Kim, S. Miyamoto","doi":"10.1109/AFSS.1996.583573","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583573","url":null,"abstract":"Basic relations and operations of fuzzy multisets which are also called fuzzy bags are newly introduced and their theoretical properties are described using a grade sequence. Application of fuzzy multisets to fuzzy relational database systems is considered: handling of fuzzy multirelations and extension of a query language are discussed.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116421807","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: 15
Automatic generation of membership functions for brain MR images 脑磁共振图像的隶属函数自动生成
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583588
Chih-Wei Chang, G. Hillman, HaoYing Ying, T. A. Kent, J. Yen
{"title":"Automatic generation of membership functions for brain MR images","authors":"Chih-Wei Chang, G. Hillman, HaoYing Ying, T. A. Kent, J. Yen","doi":"10.1109/AFSS.1996.583588","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583588","url":null,"abstract":"In this paper, we present a rule-based fuzzy segmentation system that is capable of segmenting magnetic resonance (MR) images of diseased human brains into physiologically and pathologically meaningful regions for measurement. We have developed a novel technique to automatically generate the membership functions for the fuzzy sets in the antecedent of the IF-THEN fuzzy rules in our system. Using this fuzzy system, we have performed the segmentation of brain images with periventricular lesions into four classes (grey matter, white matter, cerobrospinal fluid and periventricular lesions). The brain images were processed by our rule-based system as well as by the standard fuzzy o-means (FCM) algorithm used for performance comparison. The results, confirmed by the medical experts, showed that the rule-based fuzzy system significantly outperformed the standard FCM in the segmentation of the abnormal brain images.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123220086","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
Similarity, probability and database organisation 相似性，概率和数据库组织
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583603
A. Ramer, Hansuk Yu
{"title":"Similarity, probability and database organisation","authors":"A. Ramer, Hansuk Yu","doi":"10.1109/AFSS.1996.583603","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583603","url":null,"abstract":"The question of storing imperfect data within a database framework has been discussed in the literature almost since the time when the first formal database structure was proposed. The matter received an additional impetus with the advent of fuzzy sets and its promise of formally capturing the notion of imprecision. If the imperfection is one of uncertainty as to whether a certain data item (or data structure) is actually present in the database, then the use of probability would be natural. However, when the imperfection relates to the relative proximity of the actual data to some idealised value, the use of a fuzzy-like model (possibility or similarity) seems warranted. In practice, the choice of model appears to be a matter of personal preference for a researcher. Characteristically, there has been no attempt to utilise both possibility and probability within the same data model. This might be due, in part, to the difficulty of capturing, in a reasonable way, various interactions between the simultaneously present possibility and probability weights. This paper describes work in progress, dealing with our research in modelling the interaction between similarity among the tuples (a binary function) and the probabilities of the tuples in the relational data model. The importance of such a study is underlined by the ubiquity of situations which involve, in a natural fashion, both probabilistic and possibilistic considerations. We illustrate it on two examples.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125205217","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
A method for finding independently distributed probability models that satisfy order constraints 一种寻找满足顺序约束的独立分布概率模型的方法
Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium Pub Date : 1996-12-11 DOI: 10.1109/AFSS.1996.583628
D. Sher, B. Sy
{"title":"A method for finding independently distributed probability models that satisfy order constraints","authors":"D. Sher, B. Sy","doi":"10.1109/AFSS.1996.583628","DOIUrl":"https://doi.org/10.1109/AFSS.1996.583628","url":null,"abstract":"This research investigates a method that attempts to represent a database of expert decisions as an independent probability distribution. To implement this representation, our method searches for a simple probability model that exhibits maximum independence property and preserves a given set of inequality constraints. We show that finding such a representation can be formulated as a search problem over a log probability space with a representational complexity in a linear order of the number of variables. We show that the search can be achieved by employing linear programming technique in combination with a greedy (best first) search algorithm.","PeriodicalId":197019,"journal":{"name":"Soft Computing in Intelligent Systems and Information Processing. Proceedings of the 1996 Asian Fuzzy Systems Symposium","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128247858","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: 0
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