发布求助
文献互助 智能选刊 最新文献

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society最新文献

筛选
英文 中文
A Simple Method for Performing Type-2 Fuzzy Set Operations Based on Highest Degree of Intersection Hyperplane 一种基于最高交点超平面的二类模糊集运算的简单方法
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383873
H. Tahayori, G. D. Antoni
{"title":"A Simple Method for Performing Type-2 Fuzzy Set Operations Based on Highest Degree of Intersection Hyperplane","authors":"H. Tahayori, G. D. Antoni","doi":"10.1109/NAFIPS.2007.383873","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383873","url":null,"abstract":"Regarding the three dimensional nature of type-2 fuzzy sets their related operations are costly, in terms of time and computation, which is one of the main burdens among the popularity of type-2 fuzzy sets. In this paper we will provide a novel method for performing type-2 fuzzy set operations. We will prove that the operations would be simply performed based on the hyperplane of the highest degree of intersection of two type-1 fuzzy sets.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130567625","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: 10
Testing and Evaluating the Single Objective Intelligent Evolutionary Algorithm through a Graphic Interface 基于图形界面的单目标智能进化算法测试与评价
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383910
O. Montiel, R. Sepúlveda, O. Castillo, O. Soto
{"title":"Testing and Evaluating the Single Objective Intelligent Evolutionary Algorithm through a Graphic Interface","authors":"O. Montiel, R. Sepúlveda, O. Castillo, O. Soto","doi":"10.1109/NAFIPS.2007.383910","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383910","url":null,"abstract":"The human evolutionary model is an intelligent global optimization method conceived to perform single and multiple objective optimization, this general method is still in development, especially the multi objective (MO) part is being improved. The single objective (SO) part has demonstrated that outperforms several algorithms that are in the state of the art, for example differential evolution (DE), particle swarm optimizer, and others, we called this part single objective intelligent evolutionary algorithm (SO-IEA). The SO-IEA uses mediative fuzzy logic (MFL) for handling doubtful and contradictory information from experts to calculate the appropriated amount of individuals to create and/or to eliminate. MFL is an extension of traditional fuzzy logic and includes intuitionistic fuzzy logic (IFL) in the Atanassov sense. In this work, we are presenting the algorithm's architecture, experimental results, and a graphical interface that will help to handle the required parameters to use the SO-IEA.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132881177","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
Biomedical Spectral Classification Using Stochastic Feature Selection and Fuzzy Aggregation 基于随机特征选择和模糊聚合的生物医学光谱分类
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383865
N. Pizzi, C. Wiebe, W. Pedrycz
{"title":"Biomedical Spectral Classification Using Stochastic Feature Selection and Fuzzy Aggregation","authors":"N. Pizzi, C. Wiebe, W. Pedrycz","doi":"10.1109/NAFIPS.2007.383865","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383865","url":null,"abstract":"Classifying magnetic resonance spectra is often difficult due to the curse of dimensionality; a high-dimensional feature space couple with a small sample size. We present an aggregation strategy that combines predicted disease states from multiple classifiers with the anticipated outcome that the aggregated predictions are superior to any individual classifier prediction. Multiple classifiers are presented with different, randomly selected, subsets of spectral features. The fuzzy integration results are compared against the best individual classifier operating on a spectral feature subset.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122983290","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: 2
A Methodology for Statistical Matching with Fuzzy Logic 基于模糊逻辑的统计匹配方法
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383814
Patrick Noll, Paul Alpar
{"title":"A Methodology for Statistical Matching with Fuzzy Logic","authors":"Patrick Noll, Paul Alpar","doi":"10.1109/NAFIPS.2007.383814","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383814","url":null,"abstract":"The Analysis of data often requires information that is not available from a single source, but from multiple sources. Statistical matching procedures are methods that help to merge information from different sources into a single data set. Traditionally, statistical matching is done on the basis of computed distances between selected variables found in all data sets. Situations where no decision can be made in traditional statistical matching, e.g., in the case of identical distances, cause problems. We present a methodology for statistical matching with fuzzy logic which solves these problems. After a short introduction, the basics of traditional statistical matching are presented. The description of the theory of statistical fuzzy matching follows thereafter. The paper concludes with a short example.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126398654","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: 1
Simple Sequencing and Selection of Learning Objects using Fuzzy Inference 基于模糊推理的简单学习对象排序与选择
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383913
M. García-Valdez, Oscar Castillo, Guillermo Licea, A. Alanis
{"title":"Simple Sequencing and Selection of Learning Objects using Fuzzy Inference","authors":"M. García-Valdez, Oscar Castillo, Guillermo Licea, A. Alanis","doi":"10.1109/NAFIPS.2007.383913","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383913","url":null,"abstract":"The adaptive sequencing of learning objects defines the order in which topics (and didactic resources) in a course will be presented to learners, considering for this their previous knowledge and their particular goals. Once a sequence is proposed each topic can be supported by different didactic materials, the system must select those that are appropriate for the learner's particular needs. The challenge is that both of these tasks are based on subjective information, for example the learner knowledge, preferences, learning style, and even assessment results can be perceived differently depending the context. In this paper we propose an extension to the IMS simple sequencing specification, using fuzzy inference rules.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126572978","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
Von Mises Failure Criterion in Mechanics of Materials: How to Efficiently Use it Under Interval and Fuzzy Uncertainty 材料力学中的Von Mises失效准则:在区间和模糊不确定性下如何有效地使用它
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383903
G. Xiang, A. Pownuk, O. Kosheleva, S. Starks
{"title":"Von Mises Failure Criterion in Mechanics of Materials: How to Efficiently Use it Under Interval and Fuzzy Uncertainty","authors":"G. Xiang, A. Pownuk, O. Kosheleva, S. Starks","doi":"10.1109/NAFIPS.2007.383903","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383903","url":null,"abstract":"One of the main objective of mechanics of materials is to predict when the material experiences fracture (fails), and to prevent this failure. With this objective in mind, it is desirable to use it ductile materials, i.e., materials which can sustain large deformations without failure. Von Mises criterion enables us to predict the failure of such ductile materials. To apply this criterion, we need to know the exact stresses applied at different directions. In practice, we only know these stresses with interval or fuzzy uncertainty. In this paper, we describe how we can apply this criterion under such uncertainty, and how to make this application computationally efficient.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121019456","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: 2
Obtaining Fuzzy Sets using Mass Assignment Theory - Consistency with Interpolation - 用质量分配理论获得模糊集-与插值的一致性
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383879
A. Ralescu, S. Visa
{"title":"Obtaining Fuzzy Sets using Mass Assignment Theory - Consistency with Interpolation -","authors":"A. Ralescu, S. Visa","doi":"10.1109/NAFIPS.2007.383879","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383879","url":null,"abstract":"The problem of data summarization as fuzzy sets from frequency distributions is presented. The approach makes use of the mass assignment theory as a framework for unification of fuzzy sets and probability distributions. The approach is consistent with the interpolation of the membership function needed to infer membership degrees for data points previously not seen.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122780814","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
Towards Optimal Scheduling for Global Computing under Probabilistic, Interval, and Fuzzy Uncertainty, with Potential Applications to Bioinformatics 概率、区间和模糊不确定性下全局计算的最优调度及其在生物信息学中的潜在应用
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383894
R. Araiza, M. Taufer, M. Leung
{"title":"Towards Optimal Scheduling for Global Computing under Probabilistic, Interval, and Fuzzy Uncertainty, with Potential Applications to Bioinformatics","authors":"R. Araiza, M. Taufer, M. Leung","doi":"10.1109/NAFIPS.2007.383894","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383894","url":null,"abstract":"In many practical situations, in particular in many bioinformatics problems, the amount of required computations is so huge that the only way to perform these computations in reasonable time is to distribute them between multiple processors. The more processors we engage, the faster the resulting computations; thus, in addition to processor exclusively dedicated to this job, systems often use idle time on other processors. The use of these otherwise engaged processors adds additional uncertainty to computations. How should we schedule the computational tasks so as to achieve the best utilization of the computational resources? Because of the presence of uncertainty, this scheduling problem is very difficult not only to solve but even to formalize (i.e., to describe in precise terms). In this paper, we provide the first steps towards formalizing and solving this scheduling problem.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115874853","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: 1
Ontology-based Fuzzy Inference Agent for Diabetes Classification 基于本体的糖尿病分类模糊推理代理
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383815
Mei-Hui Wang, Chang-Shing Lee, Huan-Chung Li, Wei-Min Ko
{"title":"Ontology-based Fuzzy Inference Agent for Diabetes Classification","authors":"Mei-Hui Wang, Chang-Shing Lee, Huan-Chung Li, Wei-Min Ko","doi":"10.1109/NAFIPS.2007.383815","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383815","url":null,"abstract":"Diabetes is a chronic illness that requires continuing medical care and patient self-management to prevent acute complications and to reduce the risk of long-term complications. This paper presents an ontology-based fuzzy inference agent, including a fuzzy inference engine, and a fuzzy rule base, for diabetes classification. The diabetes disease dataset used in our study is retrieved from the UCI Machine Learning Database. The experimental results indicate that the proposed approach can work effectively for classifying the diabetes.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"220 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115246771","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: 12
Empirical and Sensor Knowledge-extraction for Fuzzy Logic Motor Control Design 模糊逻辑电机控制设计的经验和传感器知识提取
NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383911
J.L. Gonzalez-V, Oscar Castillo, L. Aguilar
{"title":"Empirical and Sensor Knowledge-extraction for Fuzzy Logic Motor Control Design","authors":"J.L. Gonzalez-V, Oscar Castillo, L. Aguilar","doi":"10.1109/NAFIPS.2007.383911","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383911","url":null,"abstract":"This paper presents a methodology for human and sensor data knowledge-extraction to assist in the design of a Fuzzy Logic Controller (FLC) when no parameterized model of the motor is available, thus it relays mainly on linguistic motor throughput description as its main data source. Proposed design methodology achieves acceptable control objective with two design stages; first, human empirical knowledge is used to specify FLC architecture and its initial parameters, employing experts' linguistic descriptions to construct controller rule base and knowledge base in accordance with cognitive map theory; Mamdani Fuzzy Inference Engine model (FIE) enables the designer to directly use empirical knowledge to create appropriate FLC by using linguistic terms to specify FLC structures. On second design stage, sensor data is use to fine-tune FLC parameters, as FLC parameters to motor control throughput relations is known by observation. The main objective of this paper is to develop a strategy of a FLC implementation capable of self-tuning, based on cognitive map theory and linguistic descriptions.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124475557","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：481959085
Book学术官方微信