{"title":"Region based fuzzy neural networks for face detection","authors":"F. Rhee, Changsu Lee","doi":"10.1109/NAFIPS.2001.944768","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944768","url":null,"abstract":"Proposes a fuzzy neural network method for face detection. In the proposed method, fuzzy membership degrees are assigned to preprocessed 20/spl times/20 window face and non-face image regions. These fuzzy membership degrees are then input to a neural network to be trained using the error backpropagation training method. After training, the output value of the neural network is interpreted as the degree of which a given window is a face or nonface region. If the window is determined to contain a face, post-processing is then performed. Experimental results show that the proposed method can detect face images more accurately than using conventional neural networks. Also, the proposed fuzzy neural network architecture is shown to require less hidden neurons than when using conventional neural networks.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130730769","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 fast genetic method for inducting linguistically understandable fuzzy models","authors":"L. Sánchez","doi":"10.1109/NAFIPS.2001.943781","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.943781","url":null,"abstract":"Fuzzy rule bases can be regarded as mixtures of experts, and boosting techniques can be applied to learn them from data. In particular, provided that adequate reasoning methods are used, fuzzy models are extended additive models, thus backfitting can be applied to them. We propose to use an implementation of backfitting that uses a genetic algorithm for fitting submodels to residuals and we also show that it is both more accurate and faster than other fuzzy rule learning methods.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130506872","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":"Why unary and binary operations in logic: general result motivated by interval-valued logics","authors":"H. Nguyen, V. Kreinovich, I. Goodman","doi":"10.1109/NAFIPS.2001.944373","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944373","url":null,"abstract":"Traditionally, in logic, only unary and binary operations are used as basic ones-e.g., \"not\", \"and\", \"or\"-while the only ternary (and higher order) operations are the operations which come from a combination of unary and binary ones. For the classical logic, with the binary set of truth values {0,1}, the possibility to express an arbitrary operation in terms of unary and binary ones is well known: it follows, e.g., from the well known possibility to express an arbitrary operation in DNF form. A similar representation result for [0,1]-based logic was proven in our previous paper. In this paper, we expand this result to finite logics (more general than classical logic) and to multi-D analogues of the fuzzy logic-both motivated by interval-valued fuzzy logics.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127966404","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":"Toward a computational environment for everyday language communication","authors":"I. Kobayashi, M. Iwazume, M. Sugeno, N. Itoi","doi":"10.1109/NAFIPS.2001.944681","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944681","url":null,"abstract":"The aim of the study is to provide all people, from small children to aged persons, with a computational environment for everyday language communication. In order to achieve this, we propose a framework for a language operating systems. The authors explain their approach to dealing with the meaning of language, the architecture of the language operating system and its components. In particular, they describe the notion of language protocol and its resource representation (i.e., semiotic base), compared to the other protocols and their resource representations. The authors argue that by processing the meaning of language rather than processing information, they attempt to provide a more humanlike computer system and an intelligent computational environment to all people.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125364238","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 rule based innovation projects estimation","authors":"A. Rotshtein, S. Shtovba, Illja Mostav","doi":"10.1109/NAFIPS.2001.944238","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944238","url":null,"abstract":"In this paper we suggest a expert system for decision making support about quality of innovation projects. The system is based on some linguistic expert rules formalized in the form of fuzzy knowledge bases. Results of decision making by the system are good concordant with expert assessments of quality.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125510844","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":"Development of model-referenced fuzzy adaptive control","authors":"Poi Loon Tang, C. D. de Silva, A. Poo","doi":"10.1109/NAFIPS.2001.943835","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.943835","url":null,"abstract":"This paper outlines the development of three different types of model-referenced adaptive control and then evaluates their performance through computer simulation. Specifically, conventional model-referenced adaptive control is used as the basis of comparison of the performance of two knowledge-based techniques. Fuzzy logic is used in the development of the knowledge base and for decision making, in the two techniques. In one knowledge-based technique, the parameters of a low-level direct digital controller are adapted so that the system tracks a reference model. In the other knowledge-based technique, the reference input to the system is adapted. Simulation studies are carried out for the three techniques, as applied to a simple nonlinear servomotor and load system. Results indicate that the knowledge-based adaptive techniques can outperform the conventional technique in specific situations.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126757951","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":"Representation, ranking, distance, and similarity of fuzzy numbers with step form membership function using k-preference integration method","authors":"Shan-Huo Chen, Chien-Chung Wang","doi":"10.1109/NAFIPS.2001.944706","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944706","url":null,"abstract":"The modified k-preference integration method is applied to treat the representation, ranking; distance and similarity of fuzzy numbers with step form membership function. First, the representation value is computed by using the modified k-preference integration method. Then two or more fuzzy numbers with step form membership function are ranked by comparing their representation values. The distance between two fuzzy numbers with step form membership function is the absolute value of the difference between their representation values, while the similarity between them can be derived from their distance. Finally, some properties regarding the representation, ranking, distance, and similarity have been proved.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126207785","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":"Engineering a front-end prototype using computing with words in generic BK-product fuzzy relational architectures","authors":"B. C. Granville, L. Kohout","doi":"10.1109/NAFIPS.2001.943771","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.943771","url":null,"abstract":"When employing fuzzy relational structures in the development of intelligent systems, a unified generic tool is needed to assist the designers, knowledge experts, and users in constructing the application's data dictionary and relational structures for the observed environment being modeled. Such a tool must apply some form of \"computing with words\" to help users conceptualize the semantics of the fuzzy relations themselves. Everyday terms and those used in special environments form a natural means of conceptualizing the reasoning process of fuzzy analysis on fuzzy relations using words rather than numbers. The recognized words and terms allow the potential users of fuzzy systems the opportunity to step back and see the big-picture of a typical application's overall relational structures and compositions. A front-end English Query Language (EQL) tool is specified along with the supporting grammar to view the emerging technologies employed in representing fuzzy relational structures and how the relational approach can be used for \"computing with words\" systems. Therefore, the desired logical analysis can be expressed using natural language queries as opposed to the mathematical products forms of the multi-valued logics used.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126394407","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 fuzzy fault diagnosis scheme with application","authors":"X. G. Wang, W. Liu","doi":"10.1109/NAFIPS.2001.943769","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.943769","url":null,"abstract":"In this paper, a new fuzzy logic diagnosis strategy is developed where the emphasis is placed upon knowledge expression and approximate reasoning. First, the fuzzy relations, between faults and symptoms, are considered as: one fault may cause several symptoms, in turn, one symptom may represent several possible faults. Second, to solve the problem that once some symptoms have been detected it is generally very difficult to attribute them to a certain fault, we employ the fuzzy relation matrix to represent these complex fault-symptom relations which are foundations of reasoning, in which the probabilities of faults are expressed as fuzzy numbers, and complex fault-symptom relations are represented with a fuzzy relation matrix whose elements are obtained by fault tree and Bayes rule. Third, upon these relations the fuzzy recognition reasoning is accomplished, which can list all faults whose possibilities of causing the occurring symptoms are greater than a certain threshold. Finally, to make the diagnostic conclusion more accurate, the fuzzy relation matrix will be appropriately revised further, based on the obtained information. The computer simulation results show that location of the malfunction is deduced by full use of the relations between faults and symptoms.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121286353","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":"Similarity-based agents for e-mail mining","authors":"V. Loia, S. Senatore, M. Sessa","doi":"10.1109/NAFIPS.2001.944289","DOIUrl":"https://doi.org/10.1109/NAFIPS.2001.944289","url":null,"abstract":"With Internet use continuing to explode, and due to the simplicity of sending e-mails to many people, recent years have seen the time spent in dealing with unnecessary and irrelevant e-mails increasing. In general, we note that the efforts of the scientific and industrial communities have been focused on the idea of smart filtering services. Our approach is different: the user wishes to send an e-mail to an appropriate reader, i.e. a user whose \"profile\" is compatible with the content of the e-mail itself. The profile is described in terms of topics that are related to the e-mail argument through a similarity-based network. The e-mail writer establishes this cognitive frame on the client-side, exploiting similarity-based reasoning. Then a search engine, based on mobile computation, is triggered: a number of autonomous agents are created and sent on to the network. The agents work as a Web-crawling spider, not exploring the net indiscriminately but searching domain-relevant documents directly on potential reader hosts. From this kind of document, the agent extracts logic-based knowledge that is processed by the similarity deduction engine. As a result, the agent returns an evaluation of the users' degree of interest in receiving the potential e-mail. On the client-side, a collector receives the different evaluations in order to define the final user mailing list by means of a flexible mechanism.","PeriodicalId":227374,"journal":{"name":"Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123043411","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}