NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society最新文献

{"title":"Multiple hybrid regression for fuzzy observed data","authors":"O. Poleshuk, E. Komarov","doi":"10.1109/NAFIPS.2008.4531224","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531224","url":null,"abstract":"A method for hybrid regression is developed in this paper. The method uses the new definition of weighted intervals. The proposed method extends group of initial data membership functions as it can be applied to (L-R) fuzzy numbers. For reliability evaluation of hybrid regression models the standard deviation, a hybrid correlation coefficient, a hybrid standard error of estimate are defined. The numerical example has demonstrated that the developed hybrid regression model can be used for analysis of relations among linguistic variables with success.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"2 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":"115599549","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 transferal of evidences derived from clinical research to single patient level: Automatic distinction of normal elderly vs. mild cognitive impairment subjects by resting EEG data processed by IFAST, a novel intelligent system","authors":"P. Rossini, M. Buscema, E. Grossi","doi":"10.1109/NAFIPS.2008.4531287","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531287","url":null,"abstract":"It has been shown that a new procedure (implicit function as squashing time, IFAST) based on artificial neural networks (ANNs) is able to compress eyes-closed resting electroencephalographic (EEG) data into spatial invariants of the instant voltage distributions for an automatic classification of mild cognitive impairment (MCI) and Alzheimer's disease (AD) subjects with classification accuracy of individual subjects higher than 92%. Here we tested the hypothesis that this is the case also for the classification of individual normal elderly (Nold) vs. MCI subjects, an important issue for the screening of large populations at high risk of AD. Eyes-closed resting EEG data (10- 20 electrode montage) were recorded in 171 Nold and in 115 amnesic MCI subjects. The data inputs for the classification by IFAST were the weights of the connections within a non linear auto-associative ANN trained to generate the instant voltage distributions of 60-s artifact free EEG data. The most relevant features were selected and coincidently the dataset was split into two halves for the final binary classification (training and testing) performed by a supervised ANN. The classification of the individual Nold and MCI subjects reached 95.87% of sensitivity and 91.06% of specificity (93.46% of accuracy). These results indicate that IFAST can reliably distinguish eyes-closed resting EEG in individual Nold and MCI subjects, and may be used for large-scale periodic screening of large populations at risk of AD and personalized care.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"50 3 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":"114346819","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":"Learning Fitts’ law with imprecise regression","authors":"M. Serrurier, M. Raynal","doi":"10.1109/NAFIPS.2008.4531265","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531265","url":null,"abstract":"The Fitts' law is used in order to predict the time for pointing a target with respect to its size and to the distance to cover. However, this law only predict the average time for pointing the target with a given difficulty. In this paper, we propose to use a fuzzy regression approach, named imprecise regression, which allows us to predict the general tendency (time with respect to the difficulty of the task), together with the imprecision associated with this tendency. In the first time we will present the imprecise regression approach. Then, we will discuss and compare the results obtained with linear regression and with fuzzy imprecise from the data obtained with a mouse pointing experimentation.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"96 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":"114841720","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":"Genetic fuzzy programs","authors":"I. Sledge, J. Keller","doi":"10.1109/NAFIPS.2008.4531236","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531236","url":null,"abstract":"When aggregating multiple items together, for processes such as decision making, it is often beneficial to assign linguistically imprecise weights to each criterion. These weights, when coupled with the values of the criteria, enable us to prioritize certain responses over others. Through the advent of fuzzy connectives, computers can also emulate this weight-biased, decision-making behavior. However, when crafting an aggregation network for a complex problem, the solution may require not just a single fuzzy aggregator, but rather multiple layers of intimately entwined fuzzy connectives. To explore a suitable hierarchical relationship, we use genetic programming, to evolve both fuzzy aggregation networks, which take the form of multiarity expression trees, and the associated connective weights. We test our evolutionary network learning approach with synthetic and real-world data sets and discuss the results.","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":"126075599","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":"Scalable fuzzy clustering algorithms","authors":"L. Hall","doi":"10.1109/NAFIPS.2008.4531356","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531356","url":null,"abstract":"Clustering is the most typical way to group unlabeled data. Today, there are very large unlabeled data sets available. Many of these data sets are too large to fit in the memory of a typical computer. Some of these data sets are so large that they can only be treated as data streams because not all of the data can be stored in a cost-effective manner. Fuzzy clustering algorithms are known to be very useful on small to medium-size data sets. This talk focuses on how to make some well understood classic fuzzy clustering algorithms scale to very large data sets and streaming data sets. The goal is to be able to create a data partition that reflects the whole data set, but requires practical computation times. In particular, we show that the fuzzy c-means families of algorithms can be scaled to provide data partitions that are very close and potentially identical to what you would get if you were able to cluster all the data. The general idea is to cluster subsets of the data and create weighted examples from the subsets. The weighted examples from a previous partition(s) are used with new data to create a new partition which reflects the examples currently loaded in memory and those partitioned previously. This process can be repeated until all the data has been clustered. Several variations on the theme of summarizing previous partitions with a set of weighted examples are given. Some history can be ignored, for example, in time changing data streams. One could also choose to cluster summarizations. Experimental data sets include several which contain tens of millions of examples, as well as streaming data sets. Results from real-world data sets show excellent partitions are obtained. For tractable size data sets it is shown that the partitions are comparable to those from fuzzy c-means when it clusters all the data.","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":"121987379","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":"Is information being denied to the scientific community by the reductionist approach to data analysis in stroke related clinical trials?","authors":"C. Helgason, M. Buscema, E. Grossi","doi":"10.1109/NAFIPS.2008.4531284","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531284","url":null,"abstract":"Background: The African American Anti platelet Stroke Prevention Study was a randomized, double-blind, investigator initiated multi-center trial of 1809 black men and women with recent non cardioembolic stroke. Its goal was to determine the efficacy and safety of two different anti platelet agents, aspirin versus ticlopidine, to prevent recurrent stroke, myocardial infarction or vascular death. The results of this study showed no statistically significant difference between the drugs with regards to combined outcome, but a difference approached significance in favor of aspirin for the outcome of stroke. Data regarding the demographics and clinical condition of each patient entered into the trial was collected, in addition to type of stroke. In a different but smaller study, \"Influence of Cyclooxygenase-1 and Glycoprotein III a Genotypes on Ex-Vivo Aspirin Response\", the genetic predisposition to aspirin resistance was determined. Again demographic and clinical data were collected on all 59 patients. Statistical analysis suggested that the PTGS1 P17L genotype contributes to aspirin response as measured by ex vivo platelet aggregation studies. Methods: We hypothesized that Auto Contractive Maps, a dynamic system created by Massimo Buscema to create a distance matrix amongst variables of interest would provide information about the relation amongst variables collected in the AAASPS study and Aspirin Response study that not only confirmed but also enriched information provided by standard statistical analysis. The Minimum Spanning tree was extracted from the distance matrix developed by Auto Contractive Maps and compared to Principal Component Analysis. Results: A Minimum Spanning Tree, the most economic way by which to represent the distance between variables, was created for the data set. Connectivity, clustering strength, degree of protection, topological entropy, Delta Hubbness, and Maximally Regular Graph were calculated. Strong links were found between variables in both studies that were missed by Principal Component Analysis. Conclusions: Clinically plausible interactions between variables collected in those patients suffering end point events in the AAASPS study were found using the dynamic non linear mapping method of Auto Contractive Maps. A new interpretation of the importance of genetic predisposition to aspirin response was found in aspirin resistant patients in the smaller clinical study of aspirin response. These connections and new findings were not discovered by PCA. A reductionist approach to data analysis in clinical trials has the potential to deprive the scientific medical community of clinically relevant information.","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":"121688444","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":"From principles of mechanics to quantum mechanics - a survey on fuzziness in scientific theories","authors":"R. Seising","doi":"10.1109/NAFIPS.2008.4531326","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531326","url":null,"abstract":"In this paper we discuss the principles of two fundamental theories of physics: mechanics and quantum mechanics. First, we consider two philosophical positions of the German physicist Heinrich Hertz. He established one of the both in the introduction of his well known Principles of Mechanics. This view - Hertz's \"picture\" concept - which has a long tradition in philosophy, particularly with regard to physics and later to other empirical sciences, serves as the starting point of an interpretation of the relationship between real systems and theoretical structures of modern science using the concept of fuzziness. This \"fuzzy view\" on philosophy of science gives particularly an interpretation of Hertz's earlier lecture on The Constitution of matter. Second we consider some principles of quantum mechanics, particularly Werner Heisenberg's uncertainty relation of subatomic object's position and momentum, and Max Born's probabilistic interpretation of the quantum mechanical wave function. These principles are parts of the so-called Copenhagen interpretation of quantum mechanics. Third, we argue that the \"fuzzy approach\" is fruitful for a \"fuzzy\" interpretation of quantum mechanics because fuzziness fills the gap between systems and phenomena in reality and the scientific theory of quantum mechanics - as every other scientific theory.","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":"124995661","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":"Reactive control of a mobile robot in a distributed environment using fuzzy logic","authors":"A. Melendez, O. Castillo, J. Soria","doi":"10.1109/NAFIPS.2008.4531341","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531341","url":null,"abstract":"This paper describes reactive control of a mobile robot using fuzzy logic in a distributed environment. Simulation results of the reactive fuzzy controller in a particular maze problem illustrate the effectiveness of the proposed approach. The mobile robot is able to solve the maze problem with the use of fuzzy rules designed with expert knowledge.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"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":"131182802","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":"Inconsistency degree computation for possibilistic description logic: an extension of the tableau algorithm","authors":"Marie-Jeanne Lesot, O. Couchariere, B. Bouchon-Meunier, J. Rogier","doi":"10.1109/NAFIPS.2008.4531240","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531240","url":null,"abstract":"Possibilistic description logic (PDL) is an extension of description logic based on possibilistic logic: it provides a framework to formalise knowledge allowing to encompass, model and handle uncertain information. In this paper, we consider the problem of consistency checking for PDL and propose an algorithm to compute the inconsistency degree of knowledge bases in this framework. To that aim, we present an extension of the tableau algorithm: we introduce extensions of the clash definition and completion rules to take into account the certainty associated with each formula, providing an inference procedure handling degree of certainty.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"517 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":"116237963","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 epistemology: The fuzziness of experimental systems","authors":"R. Seising","doi":"10.1109/NAFIPS.2008.4531330","DOIUrl":"https://doi.org/10.1109/NAFIPS.2008.4531330","url":null,"abstract":"Fuzzy sets and systems (FSS) fill the gap between scientific theories and observable real systems and phenomena. In philosophy and history of science and technology this gap carries a great potential for epistemological discussions. A new approach in this area is Hans-Jorg Rheinberger's \"historical epistemology\" dealing with the concept of \"experimental systems\". In this paper we first summarize some facts on the theory of FSS and Computational Intelligence, then we give a brief sketch of Rheinberger's \"experimental systems\", \"epistemic\" and \"technological things\", and finally we propose to combine Rheinberger's approach with FSS methodologies.","PeriodicalId":430770,"journal":{"name":"NAFIPS 2008 - 2008 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"24 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":"132263695","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}