{"title":"Sensitivity analysis through random and fuzzy sets","authors":"M. Oberguggenberger, B. Schmelzer, W. Fellin","doi":"10.1109/NAFIPS.2008.4531315","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531315","url":null,"abstract":"Sensitivity analysis has become a major tool in the assessment of the reliability of engineering structures. Given an input-output system, the question is which input variables have the most decisive influence on the output. Random and/or fuzzy sets offer a framework for modelling the data variability. Propagating random set data or fuzzy set data through a deterministic system provides a valuable impression of the output variability. The sensitivity can be assessed by pinching individual variables, changing their correlations or by varying their degree of interactivity. An important ingredient in the quantification of the changes derives from generalized information theory, namely, measures of nonspecificity, in particular, Hartley-like measures. The purpose of this contribution is to present an investigation of various methods of modelling correlations and interactivity, quantifying the results by Hartley-like measures and exhibiting a number of concrete applications in engineering.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"75 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":"130185414","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":"Impact of [0,1]-valued weights and weighted aggregation operators for possibilistic truth values","authors":"A. Bronselaer, G. Tré","doi":"10.1109/NAFIPS.2008.4531231","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531231","url":null,"abstract":"Possibilistic truth values are an elegant tool to model and reason about uncertainty concerning the (Boolean) truth value of propositions. In the framework of possibilistic truth values, aggregation operators to combine uncertainty are essential in order to make reasoning possible. This paper introduces new conjunctive and disjunctive transformations for possibilistic truth values, which are necessary to create weighted aggregation operators. Existing transformation techniques are either to strict, or they do not guarantee the normalization condition of possibility theory. The novel technique offers a best of two worlds.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"102 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":"133964456","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":"Improved iterative algorithm for computing the generalized centroid of an interval type-2 fuzzy set","authors":"K. Duran, H. Bernal, M. Melgarejo","doi":"10.1109/NAFIPS.2008.4531244","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531244","url":null,"abstract":"This paper presents an improved iterative algorithm for computing the generalized centroid of an interval type-2 fuzzy set. The properties of the discrete centroid function provide a stop condition that speeds up the original algorithm. Experimental evidence observed from three cases of study reveals that the improved algorithm is faster than the enhanced Karnik-Mendel algorithm when running over a common computing platform.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"19 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":"133726163","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":"Interval-based multi-criteria decision making: Strategies to order intervals","authors":"T. Magoc, M. Ceberio, François Modave","doi":"10.1109/NAFIPS.2008.4531298","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531298","url":null,"abstract":"Ordering alternatives in interval-based multi- criteria decision making problems is not a trivial task when the intervals of preference are overlapping. In this paper, we aim at giving a rational and natural way of ranking alternatives by computing the degrees of preference, taking into consideration the upper and lower bounds of the interval of preference as well as its width. We slightly modify the general description of degree of preference to accommodate the strategy of choice for risk-prone and risk-averse individuals as well as situations where more information is available (e.g., a probability distribution over the intervals).","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"44 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":"115613694","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":"Program synthesis from Workflow-Driven Ontologies","authors":"L. Salayandia, S. Roach, A. Gates","doi":"10.1109/NAFIPS.2008.4531306","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531306","url":null,"abstract":"An approach that results in the development of Workflow-Driven Ontologies (WDO) (called the WDO approach) allows domain scientists to capture process knowledge in the form of concepts as well as relations between concepts. Program synthesis techniques can be employed to generate algorithmic solutions by transforming the process knowledge expressed in the WDO as concepts and relations to variables and functions and computing unknown variables from known ones based on the process knowledge documented by the domain scientist. Furthermore, the algorithmic solutions that are generated by program synthesis potentially can support the composition of services, which result in the creation of executable scientific workflows. The ultimate goal of this work is to provide an end-to-end solution for scientists beginning with modeling the processes for creating work products in terminology from the scientist's own domains and ending with component-based applications that can be used to automate processes that can advance their scientific endeavors. These applications can exploit distributed components that are supported by current cyber-infrastructure efforts. This paper discusses extensions to the WDO approach that support program synthesis. To elucidate this scenario, an example related to earth sciences is presented.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"109 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":"114486780","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":"Use of fuzzy ontologies in generalization of knowledge tree results","authors":"F. Perry, R. Yager","doi":"10.1109/NAFIPS.2008.4531344","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531344","url":null,"abstract":"In this paper we examine issues involving data generalization using a fuzzy ontology. In particular we consider generalizing the results produced by the knowledge tree process from an information base.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"6 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":"114795335","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":"High frequency rough set model based on database systems","authors":"K. Vaithyanathan, T.Y. Lin","doi":"10.1109/NAFIPS.2008.4531351","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531351","url":null,"abstract":"Rough sets theory was proposed by Pawlak in the 1980s and has been applied successfully in a lot of domains. One of the key concepts of the rough sets model is the computation of core and reduct. It has been shown that finding the minimal reduct is an NP-hard problem and its computational complexity has implicitly restricted its effective applications to a small and clean data set. In order to improve the efficiency of computing core attributes and reducts, many novel approaches have been developed, some of which attempt to integrate database technologies. This paper proposes a novel approach to computing reducts called high frequency value reducts using database system concepts. The method deals directly with generating value reducts and also prunes the decision table by placing a lower bound on the frequency of equivalence values in the decision table.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"22 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":"114635154","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":"Autonomous safety decision-making in intelligent robotic systems in the uncertain environments","authors":"R. Agate, D. Seward","doi":"10.1109/NAFIPS.2008.4531262","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531262","url":null,"abstract":"This research paper presents a method to integrate safety within the decision making process of a mobile robot. For this development, RCS-RMA (real-time control system- reference model architecture) [1] is employed as an architectural framework. POMDP (partially observable Markov decision processes) model is employed at a decision making level of RCS-RMA to ensure safety from within the action selection process of an Intelligent System in the presence of uncertainty. The basic reasons for adopting this representation are initially outlined. Following this, fundamental model aspects are given, outlining the basis for the applied computational model. Experimental results and evaluation are presented in last section.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"6 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":"117350738","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":"Measuring total uncertainty in Dempster-Shafer theory of Evidence: properties and behaviors","authors":"J. Abellán, S. Moral","doi":"10.1109/NAFIPS.2008.4531312","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531312","url":null,"abstract":"In this paper, we extend the set of\" properties required for total uncertainty measures in the Dempster-Shafer theory of evidence (DST). For this purpose, we take into account properties and behaviors considered for these type of measures which have appeared in the literature. We analyze the differences between the main total uncertainty measures presented in DST in terms of their properties and behavior.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"23 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":"123492912","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 classification of metabolic brain diseases utilizing MR Spectroscopy signals","authors":"S. Z. Mahmoodabadi, J. Alirezaie, P. Babyn","doi":"10.1109/NAFIPS.2008.4531247","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531247","url":null,"abstract":"A suspected metabolic brain disorder presents a difficult challenge to the physician and the patient. We have developed a fully automated system in order to classify the Magnetic Resonance Spectroscopy (MRS) signals. Novel fuzzy rules and a fuzzy classifier have been designed in this study to categorize metabolic brain diseases in children. The sensitivity and positive predictivity of 75% plusmn 43 in detecting five metabolic brain diseases have been achieved.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"8 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":"124840155","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}