2008 4th International IEEE Conference Intelligent Systems最新文献_第10页

Model morphisms as an enabler for open visualization of product data 将模型形态作为产品数据开放可视化的推动者

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670450

B. Almeida, C. Agostinho, M. J. Nuñez-Ariño, R. Jardim-Gonçalves

引用次数: 2

Fuzzy controller for swing-up and stabilization of inverted pendulum 倒立摆起摆稳定的模糊控制器

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670408

A. Ichtev

引用次数: 3

An extension of the relational model to intuitionistic fuzzy data quality attribute model 将关系模型推广到直觉模糊数据质量属性模型

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670520

D. Boyadzhieva, B. Kolev

引用次数: 3

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670491

G. Vachkov

{"title":"Similarity analysis of images based on information granulation and fuzzy decision","authors":"G. Vachkov","doi":"10.1109/IS.2008.4670491","DOIUrl":"https://doi.org/10.1109/IS.2008.4670491","url":null,"abstract":"This paper proposes a computational scheme for fuzzy similarity analysis and classification of images that uses first an information granulation procedure followed by a subsequent fuzzy decision procedure. A special new version of the growing unsupervised learning algorithm is introduced in the paper for information granulation. It reduces the original ldquoraw datardquo (the RGB pixels) of the image to a considerably smaller number of information granules (neurons). After that two features are extracted from each image, as follows: the center-of-gravity and the weighted average size of the image. These features are further used as inputs of a special fuzzy inference procedure that computes numerically the similarity degree for a given pair if images. Finally, a sorting procedure with a predefined threshold is used to obtain the classification results for all available images. The proposed similarity and classification scheme is illustrated on the example of 18 images of flowers. It is also discussed in the paper that the appropriate tuning of the parameters of the fuzzy inference procedure is quite important for obtaining plausible, humanlike results Therefore a simple empirical process for selection of these parameters is also suggested in the paper.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117302606","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

Adaptive fuzzy control for MIMO nonlinear systems with unknown dead-zone 未知死区MIMO非线性系统的自适应模糊控制

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670425

A. Boulkroune, M. M'Saad, Mohamed Tadjine, M. Farza

引用次数: 19

Analysis of stopping criteria for the EM algorithm in the context of patient grouping according to length of stay 基于住院时间分组的EM算法停止标准分析

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670413

Revlin Abbi, E. El-Darzi, C. Vasilakis, P. Millard

{"title":"Analysis of stopping criteria for the EM algorithm in the context of patient grouping according to length of stay","authors":"Revlin Abbi, E. El-Darzi, C. Vasilakis, P. Millard","doi":"10.1109/IS.2008.4670413","DOIUrl":"https://doi.org/10.1109/IS.2008.4670413","url":null,"abstract":"The expectation maximisation (EM) algorithm is an iterative maximum likelihood procedure often used for estimating the parameters of a mixture model. Theoretically, increases in the likelihood function are guaranteed as the algorithm iteratively improves upon previously derived parameter estimates. The algorithm is considered to converge when all parameter estimates become stable and no further improvements can be made to the likelihood value. However, to reduce computational time, it is often common practice for the algorithm to be stopped before complete convergence using heuristic approaches. In this paper, we consider various stopping criteria and evaluate their effect on fitting Gaussian mixture models (GMMs) to patient length of stay (LOS) data. Although the GMM can be successfully fitted to positively skewed data such as LOS, the fitting procedure often requires many iterations of the EM algorithm. To our knowledge, no previous study has evaluated the effect of different stopping criteria on fitting GMMs to skewed distributions. Hence, the aim of this paper is to evaluate the effect of various stopping criteria in order to select and justify their use within a patient spell classification methodology. Results illustrate that criteria based on the difference in the likelihood value and on the GMM parameters may not always be a good indicator for stopping the algorithm. In fact we show that the values of the difference in the variance parameters should be used instead, as these parameters are the last to stabilise. In addition, we also specify threshold values for the other stopping criteria.","PeriodicalId":305750,"journal":{"name":"2008 4th International IEEE Conference Intelligent Systems","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132784346","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: 21

A novel approach in automatic control based on the genetic algorithm in STATCOM for improvement power system transient stability 一种基于遗传算法的STATCOM自动控制新方法，可提高电力系统暂态稳定性

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670419

G. Shahgholian, S. Eshtehardiha, H. Mahdavi-Nasab, M. Yousefi

引用次数: 26

Soft real-time view management 软实时视图管理

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670549

Elena Baralis, M. Cabutto, T. Cerquitelli, A. Garofalo, P. Garza

引用次数: 0

A statistical evaluation of neural computing approaches to predict recurrent events in breast cancer 预测乳腺癌复发事件的神经计算方法的统计评价

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670506

F. Gorunescu, M. Gorunescu, E. El-Darzi, S. Gorunescu

引用次数: 12

Information modeling for a dynamic representation of an emergency situation 用于动态表示紧急情况的信息建模

2008 4th International IEEE Conference Intelligent Systems Pub Date : 2008-11-11 DOI: 10.1109/IS.2008.4670431

F. Kebair, F. Serin

引用次数: 2