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Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society最新文献

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Fuzzy patterns recognition 模糊模式识别
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527796
B. Shukhat
{"title":"Fuzzy patterns recognition","authors":"B. Shukhat","doi":"10.1109/ISUMA.1995.527796","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527796","url":null,"abstract":"This paper is devoted to the problem of fuzzy pattern recognition. The most universal case, when both images and clusters are fuzzy sets, is considered. Based on the features of level sets, an idea of linearly separable fuzzy clusters is introduced. An algorithm is proposed for deriving a decision-making function, based on the technique originally used for the crisp case. By solving a single system of linear inequations, it allows one to derive the borders of a number of level sets of clusters. These borders, being decision functions for each level respectively, at the same time produce matching functions for fuzzy clusters. All algorithms are computer-oriented and can be implemented for the automatic recognition of fuzzy patterns.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129206314","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
Extending the application of fuzzy sets to the problem of agricultural sustainability 推广模糊集在农业可持续性问题中的应用
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527745
Elizabeth G. Dunn, James M. Keller, Leonie A. Marks, John Ikerd, P. Gader, L. D. Godsey
{"title":"Extending the application of fuzzy sets to the problem of agricultural sustainability","authors":"Elizabeth G. Dunn, James M. Keller, Leonie A. Marks, John Ikerd, P. Gader, L. D. Godsey","doi":"10.1109/ISUMA.1995.527745","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527745","url":null,"abstract":"While there is no consensus on a definition, it is widely recognized that the concept of sustainability has economic, environmental and social dimensions. This multidimensionality has impeded the development of empirical applications of the concept of sustainability. The specific problem of modeling agricultural sustainability is described. It is argued that fuzzy methods offer important advantages in overcoming at least three of the inherent difficulties in modeling agricultural sustainability: (1) the problem of noncommensurate units can be effectively handled through the use of linguistic variables; (2) information that is vague or imprecise can still be included in a problem when this information is modeled as a fuzzy set; and (3) the interrelationships between the dimensions of sustainability can be incorporated into a model by means of a fuzzy rule base. The application of fuzzy sets to the problem of agricultural sustainability is illustrated with a brief example of a mixed crop-livestock farming system in Missouri.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121797676","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: 25
Quality assurance for Monte Carlo risk assessment 蒙特卡洛风险评估的质量保证
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527662
Scott Ferson
{"title":"Quality assurance for Monte Carlo risk assessment","authors":"Scott Ferson","doi":"10.1109/ISUMA.1995.527662","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527662","url":null,"abstract":"Three major problems inhibit the routine use of Monte Carlo methods in risk and uncertainty analyses: correlations and dependencies are often ignored; input distributions are usually not available; and mathematical structure of the model is questionable. Most practitioners acknowledge the limitations induced by these problems, yet rarely employ sensitivity studies or other methods to assess their consequences. The paper reviews several computational methods that can be used to check a risk assessment for the presence of certain kinds of fundamental modeling mistakes, and to assess the possible error that could arise when variables are incorrectly assumed to be independent or when input distributions are incompletely specified.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116566203","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: 17
The use of fuzzy logic in active noise control 模糊逻辑在主动噪声控制中的应用
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527759
O. Kipersztok, Ron Hammond
{"title":"The use of fuzzy logic in active noise control","authors":"O. Kipersztok, Ron Hammond","doi":"10.1109/ISUMA.1995.527759","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527759","url":null,"abstract":"The paper describes the use of fuzzy logic for the active control of a distributed source of broadband noise modelled by multiple compact sources with low correlation between them. The early signals are collected from microphones placed near the sources. Control is provided by a cancelling noise source, in the form of a loudspeaker, between the early microphones and a control microphone placed at a location where noise reduction is desired. The fuzzy controller uses the cross correlation between early and control microphones and the signal to noise ratio of the cross correlation estimate to adjust the coefficients of a filter driving the loudspeaker. The fuzzy controller showed considerably higher noise attenuation levels when compared to the performance of an optimal linear filter controller. In addition to its ease of implementation and to making explicit the heuristic control rules, the fuzzy system localizes the control for each early microphone loudspeaker pair. The use of several, independent control units offers improved computational efficiency, which is critical for situations when the source is nonstationary, and offers the potential for parallelization.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126732765","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
Dynamic rough sets 动态粗糙集
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527709
Tom Longshaw, Sue Haines
{"title":"Dynamic rough sets","authors":"Tom Longshaw, Sue Haines","doi":"10.1109/ISUMA.1995.527709","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527709","url":null,"abstract":"Describes how fuzzy rough sets can be used as the underlying model for a semantics which describes uncertainty. This representation prevents the explosion in complexity normally associated with uncertainty. The approximation is suitable for establishing safety properties of dynamic systems which Monte Carlo techniques cannot. This paper examines the underlying mathematics and describes some of the fundamental operations of the semantics. It briefly demonstrates some of the ways we have applied the semantics and defines an efficiency measure for these rough sets which can measure the amount of information lost by any approximation.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125177189","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
Uncertainty analysis of multiple epidemiological studies using frequency distributions of relative risks 使用相对风险频率分布的多个流行病学研究的不确定性分析
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527666
A. Shlyakhter
{"title":"Uncertainty analysis of multiple epidemiological studies using frequency distributions of relative risks","authors":"A. Shlyakhter","doi":"10.1109/ISUMA.1995.527666","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527666","url":null,"abstract":"A new format for presenting uncertainty in the results of multiple epidemiologic studies of the same outcome is suggested. A set of 95% confidence intervals for relative risk, RR, is transformed to a frequency distribution of the normalized deviations, ln(RR)/SE(ln(RR)), from the null value In(RR)=0 (RR=1). It is assumed that deviations from RR=1 are due to unaccounted residual biases and we compare the distribution of these deviations with the distributions of the actual errors in physical measurements where the true values have subsequently become known, and the incidence of large errors can be estimated. Comparison of these distributions can, by analogy, help to understand how convincing is the evidence of elevated risk in observational studies.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128140155","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
Belief updating 信念更新
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527782
A. Slobodová
{"title":"Belief updating","authors":"A. Slobodová","doi":"10.1109/ISUMA.1995.527782","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527782","url":null,"abstract":"Uncertainty is present in most tasks that require intelligent behaviour. Probability theory has by far the longest tradition in problems connected with uncertainty, but the Dempster-Shafer theory provides more general model. A central problem of this theory is conditioning. M. Spies's paper (1994) presents a new approach to a solution of this problem, by establishing a link between conditional events and discrete random sets. Conditional events were introduced as sets of equivalent events under conditioning. These sets are targets of a multivalued mapping and conditional belief functions were introduced. We study properties of these functions in the cases that belief functions were obtained by Bayesian conditioning from an unconditional belief function.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128192282","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
Tail effects of uncertainty modeling in QRA QRA中不确定性建模的尾部效应
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527682
M. Maes, L. Huyse
{"title":"Tail effects of uncertainty modeling in QRA","authors":"M. Maes, L. Huyse","doi":"10.1109/ISUMA.1995.527682","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527682","url":null,"abstract":"The paper discusses the general feeling of uneasiness engineers and scientists experience when they assume probability models for basic uncertainties governing a risk or reliability analysis. Specifically, the aspect of tail behaviour is addressed. It is well known that quantitative risk estimation is critically dependent on the tail behavior. The present paper focuses an tail heaviness and the effect of tail heaviness of basic uncertainties on the overall risk or failure probability. This is of interest to a model-based risk analysis as well as a structural reliability analysis. Two examples are included to illustrate some of the concepts introduced.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"224 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130694308","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
Reliability-based design of unstiffened panels for ship structures 船舶结构无加筋板的可靠性设计
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527778
I. Assakkaf, B. Ayyub
{"title":"Reliability-based design of unstiffened panels for ship structures","authors":"I. Assakkaf, B. Ayyub","doi":"10.1109/ISUMA.1995.527778","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527778","url":null,"abstract":"The main objective of structural design is to insure safety, function, and performance of an engineering system for target reliability levels and for specified time period. As this must be accomplished under conditions of uncertainty, probabilistic analyses are necessary in the development of such probability-based design of unstiffened panels for ship structures. The load and resistance factor design (LRFD) format was developed in this paper for unstiffened panels. Partial safety factors were determined to account for the uncertainties in strength and load effects. In developing these factors, Monte Carlo simulation was utilized to assess the probabilistic characteristics of strength models by generating basic random variables that define the strength and substituting them in these models; and the first-order reliability method (FORM) was used to determine the partial safety factors based on prescribed probabilistic characteristics of load effects. Also, strength factors were computed for a set of load factors to meet a target reliability level.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130571215","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
Self-learning fuzzy control of civil structures 土木结构的自学习模糊控制
Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society Pub Date : 1995-03-17 DOI: 10.1109/ISUMA.1995.527668
L. Faravelli, T. Yao
{"title":"Self-learning fuzzy control of civil structures","authors":"L. Faravelli, T. Yao","doi":"10.1109/ISUMA.1995.527668","DOIUrl":"https://doi.org/10.1109/ISUMA.1995.527668","url":null,"abstract":"The application of ANFIS (Adaptive Network-based Fuzzy Inference System) to the fuzzy control of structures was investigated by the authors in a earlier paper (L. Faravelli and T. Yao, 1994). Through neural network learning, ANFIS can be trained to replace an existing fuzzy controller. The resulting controller makes use of the more efficient Takagi-Sugeno inference scheme instead of COG (center of gravity) and is inherently computationally faster. The next logical step accomplished in this paper is to implement the trajectory adaptive networks (TAN) and stage adaptive networks (SAN) that were proposed to be used with temporal back propagation to achieve a self learning fuzzy controller. This approach should result in a fuzzy controller that is optimized to handle loads of the type used in the self learning training. Because the learning process is goal directed (i.e., a zero vector is the desired displacement behavior), some optimization is introduced.","PeriodicalId":298915,"journal":{"name":"Proceedings of 3rd International Symposium on Uncertainty Modeling and Analysis and Annual Conference of the North American Fuzzy Information Processing Society","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133378978","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: 8
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