{"title":"Beyond intervals: Phase transitions lead to more general ranges","authors":"K. Villaverde, Gilbert Ornelas","doi":"10.1109/NAFIPS.2008.4531309","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531309","url":null,"abstract":"One of the main tasks of science and engineering is to use the current values of the physical quantities for predicting the future values of the desired quantities. Due to the (inevitable) measurement inaccuracy, we usually know the current values of the physical quantities with interval uncertainty. Traditionally, it is assumed that all the processes are continuous; as a result, the range of possible values of the future quantities is also known with interval uncertainty. However, in many practical situations (such as phase transitions), the dependence of the future values on the current ones becomes discontinuous. We show that in such cases, initial interval uncertainties can lead to arbitrary bounded closed ranges of possible values of the future quantities. We also show that the possibility of such a discontinuity may drastically increase the computational complexity of the corresponding range prediction problem.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115141095","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 choquet integral-based multi-class classifier and its applications on the prediction of membrane protein types","authors":"Carlos Campos, Lourdes Pelayo","doi":"10.1109/NAFIPS.2008.4531324","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531324","url":null,"abstract":"In this paper, a novel aggregator information-based strategy for predicting membrane proteins types is introduced. In particular, we propose a framework of five Choquet Integrals (one Choquet Integral for each protein type) that are specialized to compute the global score of each class of proteins. These global scores are obtained by the combination of the partial evaluations of several membrane protein features provided by different individual classifiers. To compute the fuzzy measures associated with each Choquet Integral, we use a new unsupervised method (International Journal of Intelligent Systems, January 2008) proposed in the literature in which the concept of importance of attributes (in our case, the importance of the subsets of the classifiers) is replaced by that of information content in the subsets of classifiers. The parameters of the individual classifiers are adjusted with a conventional training dataset of 2059 sequences of aminoacids where 435 are Type I, 152 Type II, 1311 are multipass trans-membrane, 51 lipid-chain-anchored and 110 GPI-anchored type. The results obtained in this experiment, shows that our proposed method obtains a higher classification accuracy compared with the results obtained for several methods cited in the literature.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115268941","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":"Measures of uncertainty and uncertainty-based information in GIT: A historical overview","authors":"G. Klir, A. Bronevich","doi":"10.1109/NAFIPS.2008.4531310","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531310","url":null,"abstract":"As an introduction to the special session on generalized information theory (GIT), a historical overview is presented in this paper of major results regarding justifiable measures of uncertainty for the various theories of imprecise probabilities.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121063966","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":"How to measure a degree of mismatch between probability models, p-boxes, etc.: A decision-theory-motivated utility-based approach","authors":"L. Longpré, S. Ferson, W. T. Tucker","doi":"10.1109/NAFIPS.2008.4531299","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531299","url":null,"abstract":"Different models can be used to describe real-life phenomena: deterministic, probabilistic, fuzzy, models in which we have interval-valued or fuzzy-valued probabilities, etc. Models are usually not absolutely accurate. It is therefore important to know how accurate is a given model. In other words, it is important to be able to measure a mismatch between the model and the empirical data. In this paper, we describe an approach of measuring this mismatch which is based on the notion of utility, the central notion of utility theory. We also show that a similar approach can be used to measure the loss of privacy.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127500580","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":"The class of nearest belief functions to a given probability measure","authors":"A. Lepskiy","doi":"10.1109/NAFIPS.2008.4531317","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531317","url":null,"abstract":"The paper is devoted to the solution of two problems. The first one consists of finding a probability measure which deviates at root-mean-square from a given belief function. The other problem is the inverse one, that is for a given probability measure it is necessary to find a class of belief functions which deviate at root-mean-square from a given probability measure. We find a description of the class of nearest belief functions in the form of system inequalities and indicate a subset of extreme points of this class.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128912860","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":"An experimental comparison of various aggregation operators in a fuzzy information retrieval model","authors":"K. Nowacka, S. Zadrożny, J. Kacprzyk","doi":"10.1109/NAFIPS.2008.4531242","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531242","url":null,"abstract":"In this paper, we present the results of an experimental comparison of various aggregation operators used in a fuzzy information retrieval model we have recently proposed. The essence of this model is the use of Zadeh's linguistic statements to represent the documents and queries and then to determine their degree of matching. This leads to the use of the minimum operator but in computational experiments it does not work well. Thus other operators are proposed to replace the minimum and the computational results are shown and discussed.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"35 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130493388","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":"Mixed Fuzzy Functions","authors":"I. Burhan Turksen, Canada Grant","doi":"10.1109/NAFIPS.2008.4531343","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531343","url":null,"abstract":"Mixed-fuzzy functions are proposed as an alternate to fuzzy rule base formation in the structure identification of system models and reasoning with them. These mixed-fuzzy functions can be determined by any function identification method such as least squares' estimates, LSE, maximum likelihood estimates, MLE, support vector machines, SVM, etc. For this purpose, working knowledge of a fuzzy clustering algorithm such as FCM or its variations, such as Improved fuzzy clustering method (IFCM), would be sufficient to obtain membership values of input vectors. The membership values together with scalar input variables are then used by the LSE technique to determine \"mixed fuzzy functions\" for each cluster identified by FCM and/IFCM. These functions are different from \"fuzzy rule base\" approaches as well as \"fuzzy regression\" approaches. In mixed fuzzy functions, various transformations of the membership values are included as new variables in addition to original selected scalar input variables; and at times, a logistic transformation of non-scalar original selected input variables may also be included as a new variable.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"214 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114094920","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":"Neural Network optimization with a hybrid evolutionary method that combines Particle Swarm and Genetic Algorithms with fuzzy rules","authors":"F. Valdez, P. Melin","doi":"10.1109/NAFIPS.2008.4531335","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531335","url":null,"abstract":"We describe in this paper a new hybrid evolutionary method that combines PSO and GA with fuzzy rules for the optimization of the topology of a Neural Network (NN) for the problem of face recognition. In this case, we used the Yale face database for training the Neural Network. The new evolutionary method combines the advantages of PSO and GA to give us an improved PSO+GA hybrid method. Fuzzy Logic is used to combine the results of the PSO and GA in the best way possible.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126230305","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":"Asymmetric paternalism: Description of the phenomenon, explanation based on decisions under uncertainty, and possible applications to education","authors":"O. Kosheleva, François Modave","doi":"10.1109/NAFIPS.2008.4531301","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531301","url":null,"abstract":"In general, human being are rational decision makers, but in many situations, they exhibit unexplained \"inertia\", reluctance to switch to a better decision. In this paper, we show that this seemingly irrational behavior can be explained if we take uncertainty into account; we also explain how this phenomenon can be utilized in education.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126273507","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}
R. Araiza, M. Ceberio, Naga Suman Kanagala, V. Kreinovich
{"title":"Applications of 1-D versions of image referencing techniques to hydrology and to patient rehabilitation","authors":"R. Araiza, M. Ceberio, Naga Suman Kanagala, V. Kreinovich","doi":"10.1109/NAFIPS.2008.4531295","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531295","url":null,"abstract":"In this paper, we consider two seemingly unrelated problems: the hydrology problem of relation between groundwater and surface water, and a problem of identification of human gait in neuro-rehabilitation. It turns out that in both problems, we can efficiently use soft computing-motivated algorithms originally developed for image referencing.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115796263","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}