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FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)最新文献

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Evaluation of an IGA-based image retrieval system using wavelet coefficients 基于iga的图像检索系统的小波系数评价
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-12-01 DOI: 10.1109/FUZZY.1999.790176
H. Takagi, Sung-Bae Cho, T. Noda
{"title":"Evaluation of an IGA-based image retrieval system using wavelet coefficients","authors":"H. Takagi, Sung-Bae Cho, T. Noda","doi":"10.1109/FUZZY.1999.790176","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.790176","url":null,"abstract":"We evaluate the performance of an interactive genetic algorithm (IGA)-based image retrieval system with a subjective test. First, the IGA-based system that retrieves images based on wavelet analysis is introduced. Second, a psychological scale space is constructed to quantitatively express mental images to handle subjective retrieval. Third, the IGA-based system is compared with a random search-based system using the psychological space and a subjective test. The two sign tests and a statistical test have shown that the IGA-based system is significantly quicker in image retrieval than a random search-based image retrieval system.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130740957","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: 30
Neural network cubes (N-cubes) for unsupervised learning in gray-scale noise 灰度噪声下无监督学习的神经网络立方体(N-cubes)
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-12-01 DOI: 10.1109/FUZZY.1999.793204
Hoon Kang, Won-Hee Lee
{"title":"Neural network cubes (N-cubes) for unsupervised learning in gray-scale noise","authors":"Hoon Kang, Won-Hee Lee","doi":"10.1109/FUZZY.1999.793204","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.793204","url":null,"abstract":"We consider a class of auto-associative memories, namely, N-Cubes (neural-network cubes) in which 2D gray-level images and hidden sinusoidal 1D wavelets are stored in cubical memories. First, we develop a learning procedure based upon the least-squares algorithm. Therefore, each 2D training image is mapped into the associated 1D waveform in the training phase. Next, we show how the recall procedure minimizes errors among the orthogonal basis functions in the hidden layer. As a 2D image corrupted by noise is applied to an N-Cube, the nearest one of the originally stored training images would be retrieved in the recall phase. Simulation results confirm the efficiency and the noise-free properties of N-Cubes.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126265333","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
New method of dealing with partially inconsistent rule bases for fuzzy logic controller 模糊逻辑控制器部分不一致规则库处理的新方法
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-08-22 DOI: 10.1109/FUZZY.1999.793283
Jae-Soo Cho, Dong-Jo Park
{"title":"New method of dealing with partially inconsistent rule bases for fuzzy logic controller","authors":"Jae-Soo Cho, Dong-Jo Park","doi":"10.1109/FUZZY.1999.793283","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.793283","url":null,"abstract":"A novel method of fuzzy logic control based on possibly inconsistent if-then rules representing uncertain knowledge or imprecise data is studied. When it is hard to obtain consistent rule bases, we propose a fuzzy logic control based on weighted rules depending on output performances using a neural network and we derive a weight updating algorithm. To guarantee convergence of the weights, a learning rate is developed by introducing a Lyapunov function. With the final weight change information, we can make better decisions by taking into consideration conflicting rules. The proposed method is applied to simple problems and simulation results are included. And real applications of the proposed method are also discussed.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115303003","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
Fuzzy associative memory-driven approach to knowledge integration 模糊联想记忆驱动的知识整合方法
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-08-22 DOI: 10.1109/FUZZY.1999.793254
Myoung-Jong Kim, Ingoo Han, K. Lee
{"title":"Fuzzy associative memory-driven approach to knowledge integration","authors":"Myoung-Jong Kim, Ingoo Han, K. Lee","doi":"10.1109/FUZZY.1999.793254","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.793254","url":null,"abstract":"We propose a knowledge integration mechanism that yields a cooperated knowledge by integrating user knowledge, expert knowledge and machine knowledge within the fuzzy logic-driven framework, and then refines it with a fuzzy associative memory (FAM) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Experimental results show that the FAM-driven approach can enhance the reasoning performance by refining the cooperated knowledge of fuzzy logic-driven framework. This result means that the FAM-driven approach can be a robust guidance for knowledge integration.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125853754","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: 4
A software safety evaluation method based on fuzzy colored Petri nets 基于模糊着色Petri网的软件安全评价方法
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-08-22 DOI: 10.1109/FUZZY.1999.793056
H. Son, P. Seong
{"title":"A software safety evaluation method based on fuzzy colored Petri nets","authors":"H. Son, P. Seong","doi":"10.1109/FUZZY.1999.793056","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.793056","url":null,"abstract":"The objective of the paper is to present a safety evaluation method. Fuzzy colored Petri nets (FCPN), which are a fuzzy Petri net model based on colored Petri nets, are introduced as the basis of the evaluation. FCPN prove to be useful to evaluate software safety through the safety evaluation method proposed in this work.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129459164","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 observer approach to automatic recognition of happiness using facial wrinkle features 基于面部皱纹特征的模糊观察者幸福度自动识别
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-08-22 DOI: 10.1109/FUZZY.1999.790139
Gyu-tae Park, Z. Bien
{"title":"Fuzzy observer approach to automatic recognition of happiness using facial wrinkle features","authors":"Gyu-tae Park, Z. Bien","doi":"10.1109/FUZZY.1999.790139","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.790139","url":null,"abstract":"The problem of recognizing human facial expressions of emotion such as \"happiness\" is addressed and the soft computing techniques of fuzzy logic and artificial neural networks are employed as an approach for efficient recognition. The proposed recognition system has a three layered architecture: at the high level, a fuzzy system is designed based on human linguistic expressions; at the mid level, a fuzzy observer is proposed to indirectly estimate the linguistic variables using available image features; while at the low level, image features are extracted to characterize the facial features. A multilayered neural network is employed to develop parameter adjustment of the fuzzy observer based on available crisp input-fuzzy output sample sets. Spectral features using the slice DFT are adopted as image features that characterize facial wrinkles of the nasolabial folds. Experimental results performed on a real image sequence are presented to demonstrate the effectiveness and efficiency of the proposed approach.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132995953","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: 6
Design of gradient descent based self-organizing fuzzy logic controller with dual outputs 基于梯度下降的双输出自组织模糊控制器设计
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-08-22 DOI: 10.1109/FUZZY.1999.793284
Sang-Ho So, Dong-Jo Park
{"title":"Design of gradient descent based self-organizing fuzzy logic controller with dual outputs","authors":"Sang-Ho So, Dong-Jo Park","doi":"10.1109/FUZZY.1999.793284","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.793284","url":null,"abstract":"A new self-organizing fuzzy logic controller based on the gradient-descent method is presented. To implement the proposed algorithm, a new performance function is defined and analyzed by representing the gradient vector field. From this analysis, we propose the gradient-descent based algorithm with performance measure that can ensure a generalized performance decision table. To verify the performance of the proposed controller, we simulated it on the pendulum system driven with a DC-servo motor.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123658445","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
Fuzzy control of nonlinear systems using two standard techniques 非线性系统的模糊控制采用两种标准技术
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-08-22 DOI: 10.1109/FUZZY.1999.793064
R. Boukezzoula, S. Galichet, L. Foulloy
{"title":"Fuzzy control of nonlinear systems using two standard techniques","authors":"R. Boukezzoula, S. Galichet, L. Foulloy","doi":"10.1109/FUZZY.1999.793064","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.793064","url":null,"abstract":"The problem of the control of discrete-time nonlinear systems for which there is no available analytic model is tackled in this paper. Based on the ability of fuzzy systems to approximate any nonlinear mapping, the unknown nonlinear system is represented by a Takagi-Sugeno fuzzy model which is identified using input-output data. The control problem is then solved using a standard technique. Two different approaches are considered in this paper. The first one is a version of input-output linearization of discrete-time nonlinear systems. The advantage of this technique is the possibility to attenuate the influence of unstructured uncertainties on the control performances by introducing an additive control component. The second developed strategy is internal model control which is based on the introduction of an explicit fuzzy model of the plant in the control structure. Perfect control is obtained when the controller is chosen as the inverse of the fuzzy model. Finally, simulation results are included to demonstrate the feasibility of both proposed methods.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121538085","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: 5
Convergence adjustment of deflection yoke using soft computing techniques 利用软计算技术进行偏转轭的收敛调整
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-08-22 DOI: 10.1109/FUZZY.1999.793298
Won-Kyung Song, Joo-Han Kim, W. Bang, Sungwon Joo, Z. Bien, Sangbong Park
{"title":"Convergence adjustment of deflection yoke using soft computing techniques","authors":"Won-Kyung Song, Joo-Han Kim, W. Bang, Sungwon Joo, Z. Bien, Sangbong Park","doi":"10.1109/FUZZY.1999.793298","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.793298","url":null,"abstract":"A high quality deflection yoke (DY) is an essential factor for a high quality monitor. Currently, the DY adjustment process is done manually by attaching ferrite sheets on the inside surface of the DY. In this paper, we deal with the convergence adjustment algorithms employed in the guidance system. An inference engine that is based on soft computing techniques is proposed to systematically deal with several resources including the expert's knowledge in the convergence adjustment process of the DY. In our approach, the rough set theory is used to handle the input/output data collections of the DY adjustment, and the fuzzy logic and evolutionary programming are used to model the plant and to tune the model. With the given initial convergence, a rough set driven coarse search part finds a coarse area and then more precise positions are searched and decided in the fuzzy inference engine driven fine search part. Initial experimental results show that the proposed algorithm works well in the real convergence adjustment process of the DY.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"86 1-2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116914806","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: 7
Self-organizing fuzzy inference system by Q-learning 基于q学习的自组织模糊推理系统
FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315) Pub Date : 1999-08-22 DOI: 10.1109/FUZZY.1999.793268
Min-Soeng Kim, Sun-Gi Hong, Jujang Lee
{"title":"Self-organizing fuzzy inference system by Q-learning","authors":"Min-Soeng Kim, Sun-Gi Hong, Jujang Lee","doi":"10.1109/FUZZY.1999.793268","DOIUrl":"https://doi.org/10.1109/FUZZY.1999.793268","url":null,"abstract":"The fuzzy inference system (FIS) is an expert system based on if-then rules which are extracted from experts' knowledge. To obtain experts' knowledge, however, is not always easy and may be expensive. Q-learning is one type of reinforcement learning in which the desired sequence of actions can be obtained by trial and error without a priori knowledge about the model. In this paper, the extended rule and the interpolation technique are proposed to combine FIS and Q-learning. The resulting self-organizing fuzzy inference system by Q-learning (SOFIS-Q) has the capability of generating the fuzzy rule base automatically and on-line by trial and error without any experts' knowledge.","PeriodicalId":344788,"journal":{"name":"FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134504845","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: 10
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