NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society最新文献_第4页

On Learning Decision Rules From Flow Graphs 从流图中学习决策规则

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383918

Chien-Chung Chan, S. Tsumoto

引用次数: 5

A Comparison of Computational Efforts between Particle Swarm Optimization and Genetic Algorithm for Identification of Fuzzy Models 粒子群算法与遗传算法在模糊模型识别中的计算量比较

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383845

A. Khosla, S. Kumar, K.R. Ghosh

{"title":"A Comparison of Computational Efforts between Particle Swarm Optimization and Genetic Algorithm for Identification of Fuzzy Models","authors":"A. Khosla, S. Kumar, K.R. Ghosh","doi":"10.1109/NAFIPS.2007.383845","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383845","url":null,"abstract":"Fuzzy systems are rule-based systems that provide a framework for representing and processing information in a way that resembles human communication and reasoning process. Fuzzy modeling or fuzzy model identification is an arduous task, demanding the identification of many parameters that can be viewed as an optimization process. Evolutionary algorithms are well suited to the problem of fuzzy modeling because they are able to search complex and high dimensional search space while being able to avoid local minima (or maxima). The particle swarm optimization (PSO) algorithm, like other evolutionary algorithms, is a stochastic technique based on the metaphor of social interaction. PSO is similar to the genetic algorithm (GA) as these two evolutionary heuristics are population-based search methods. The main objective of this paper is to present the tremendous savings in computational efforts that can be achieved through the use of PSO algorithm in comparison to GA, when used for the identification of fuzzy models from the available input-output data. For realistic comparison, the training data, models complexity and some other common parameters that influence the computational efforts considerably are not changed. The real data from the rapid nickel-cadmium (Ni-Cd) battery charger developed has been used for the purpose of illustration and simulation purposes.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"23 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":"128241156","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: 27

Identification of Rigid-Body Dynamics of Robotic Manipulators Using Type-2 Fuzzy Logic Filter 基于2型模糊逻辑滤波器的机械臂刚体动力学辨识

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383870

Qun Ren, Z. Qin, L. Baron, L. Birglen, M. Balazinski

引用次数: 3

A Fuzzy Model for the Evaluation of Efficacy of Continuous Positive Airway Pressure (CPAP) Treatment 持续气道正压治疗(CPAP)疗效评价的模糊模型

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383862

M. Kwiatkowska, A. Idzikowski, L. Matthews

{"title":"A Fuzzy Model for the Evaluation of Efficacy of Continuous Positive Airway Pressure (CPAP) Treatment","authors":"M. Kwiatkowska, A. Idzikowski, L. Matthews","doi":"10.1109/NAFIPS.2007.383862","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383862","url":null,"abstract":"Obstructive sleep apnea hypopnea (OSAH) is a serious, chronic respiratory disorder afflicting approximately 2-4% of the general population. The standard treatment of OSA is the continuous positive airway pressure (CPAP). CPAP treatment is highly effective; however, it is not curative and its efficacy depends highly on patient's life-long compliance. Modeling of the effectiveness of this therapy involves several interrelated and, often, subjective factors. This paper describes a model, called CPAP-VAL, for the evaluation of CPAP treatment based on three main factors: improvements in symptoms (nocturnal blood oxygen desaturation, excessive daytime sleepiness, hypertension, and depressive moods), CPAP treatment compliance (average hours of use, percentage of days used, and percentage of CPAP use per total hours of sleep), and patient's characteristics (age, gender, and OSAH severity). The proposed model uses the fuzzy logic approach to combine subjective and objective measurements and to represent complex interrelationships between various factors. The CPAP-VAL model was designed as an evaluation component for a telehealth system, CPAP-T*MONITOR, which will support the treatment process for OSAH patients living in the rural areas.","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":"128736191","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

EHSS Velocity Control by Fuzzy Neural Networks 模糊神经网络控制EHSS速度

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383803

S.A. Mohseni, M. Aliyari, M. Teshnehlab

引用次数: 12

A Note on Continuity and Semicontinuity of Fuzzy Mappings 关于模糊映射的连续性和半连续性的注记

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383820

Yu-Ru Syau, L. Sugianto, E. Lee

引用次数: 2

Conceptual Summaries as Query Answers 作为查询答案的概念摘要

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383883

H. Bulskov, T. Andreasen, T. V. Terney

引用次数: 2

A Comparison of the Measure of Surprise Between Several Variables for Medical Control 医学控制中几个变量间惊喜度量的比较

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383878

C. Helgason, T. Jobe

{"title":"A Comparison of the Measure of Surprise Between Several Variables for Medical Control","authors":"C. Helgason, T. Jobe","doi":"10.1109/NAFIPS.2007.383878","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383878","url":null,"abstract":"The fuzzy causation measure K has be defined using the fuzzy Subsethood theorem. It is a measure of the role of unknown factors in the determination of a change in cardinality of a fuzzy set. Methods: We measured the value of K for: (1) change in fuzzy set cardinality using low density and high density lipoprotein values in 10 patients with history of ischemic stroke, (2) the change in fuzzy set cardinality for expert opinion regarding the degree of goal value attained by same variables, and (3) the change in fuzzy cardinality for non-expert grading of degree of control of the same variables. We compared K values for change in lab results, expert results and non expert results. Results: The degree of change in K for low and high density lipoprotein values in each of 10 patients, and the non expert was minimal compared to that of the expert's opinion. Conclusion and Interpretation: The expert and the non expert use their own normalization values for determination of degree of clinical goal values met for a given laboratory result. In the case of the expert, this normalization changes based on his experience and in a non linear fashion. For the non expert who normalizes according to a set standard of written clinical guidelines, there is no change in K reflecting a rigid standard canceling out the effect of any other contributing factors on his judgment.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"169 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":"134086019","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

A Comparative Study between an Offline and an Online Fuzzy Model 离线与在线模糊模型的比较研究

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383847

I. Luna, S. Soares, R. Ballini

{"title":"A Comparative Study between an Offline and an Online Fuzzy Model","authors":"I. Luna, S. Soares, R. Ballini","doi":"10.1109/NAFIPS.2007.383847","DOIUrl":"https://doi.org/10.1109/NAFIPS.2007.383847","url":null,"abstract":"This paper suggests and compares two approaches for building a fuzzy-rule based system for time series modeling and forecasting. The first one is based on a constructive offline learning (C-FSM). The second one, is based on an adaptive online learning process (A-FSM). Both models have its general architecture based on a fuzzy rule based system, and its respective learning algorithms are based on the EM optimization technique. Because the C-FSM is trained in an offline learning, it results in a more accurate model. However, the A-FSM has a faster learning process, since it is not necessary to retrain it with all data available at each iteration. The A-FSM also provides a more compact structure, being its learning and structure generation, great advantages in terms of time process and computational effort, when compared to the constructive approach. Results applying both techniques for building time series models show their efficiency, having each one of them important advantages when compared. The constructive offline model gets better accuracy, but, the online one, has a faster learning and a provides a simpler final structure.","PeriodicalId":292853,"journal":{"name":"NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society","volume":"136 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":"133105259","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

Detecting Duplicates in Geoinformatics: from Intervals and Fuzzy Numbers to General Multi-D Uncertainty 地理信息学中的重复检测:从区间和模糊数到一般多维不确定性

NAFIPS 2007 - 2007 Annual Meeting of the North American Fuzzy Information Processing Society Pub Date : 2007-06-24 DOI: 10.1109/NAFIPS.2007.383900

S. Starks, L. Longpré, R. Araiza, V. Kreinovich, Hung T. Nguyen

引用次数: 0