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2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)最新文献

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Image Color Reduction Based on Self-Organizing Maps and Growing Self-Organizing Neural Networks 基于自组织映射和生长自组织神经网络的图像色彩还原
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.34
Guojian Cheng, Jinquan Yang, Kuisheng Wang, Xiaoxiao Wang
{"title":"Image Color Reduction Based on Self-Organizing Maps and Growing Self-Organizing Neural Networks","authors":"Guojian Cheng, Jinquan Yang, Kuisheng Wang, Xiaoxiao Wang","doi":"10.1109/HIS.2006.34","DOIUrl":"https://doi.org/10.1109/HIS.2006.34","url":null,"abstract":"Color is one of the most important properties for object detection. Color Reduction of Image (CRI) is an important factor for segmentation, compression, presentation and transmission of images. The main purpose of CRI is to cut off the image storage spaces and computation time. Kohonen¿s Self-Organizing Maps (KSOM) can generate mappings from high-dimensional signal spaces to lower dimensional topological structures. The main characteristics of KSOM are formation of topology preserving feature maps and approximation of input probability distribution. Growing Self-Organizing Neural Network (GSONN) has got more and more attentions in the past decade, to overcome some limitations of KSOM. An effective approach to solve CRI problem is to consider it as a clustering problem and solve it by using some adaptive clustering methods, such as KSOM and GSONN. This paper first gives an introduction to KSOM and neural gas network. Then, we discuss a typical GSONN, growing neural gas. After that, a performance comparison of KSOM and GSONN for CRI is given. It is ended with some conclusions.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128826092","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: 11
Automatic T-Mixture Model Selection via Rival Penalized EM 基于对手惩罚EM的t型混合动力车自动选择
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.14
Chunyan Zhang, Jin Tang, B. Luo
{"title":"Automatic T-Mixture Model Selection via Rival Penalized EM","authors":"Chunyan Zhang, Jin Tang, B. Luo","doi":"10.1109/HIS.2006.14","DOIUrl":"https://doi.org/10.1109/HIS.2006.14","url":null,"abstract":"Modelling mixtures of multivariate t-distributions are usually used instead of Gaussian mixture models(GMM) as a robust approach, when one fits a set of continuous multivariate data which have wider tail than Gaussian¿s or atypical observations, but it is unable to perform model selection automatically through the traditional EM (Expectation Maximization) algorithm. To solve this problem, a new algorithm, which is called Rival Penalized Expectation-Maximization (RPEM) algorithm, is proposed to t-mixture model (TMM). It can automatically select an appropriate number of densities in t-density mixture model. Experimental results on unsupervised color image segmentation demonstrate the affectivity of the proposed algorithm.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127295652","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
Dynamic Artificial Neural Networks for Centroid Prediction in Astronomy 用于天文质心预测的动态人工神经网络
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.22
S. Weddell, R. Webb
{"title":"Dynamic Artificial Neural Networks for Centroid Prediction in Astronomy","authors":"S. Weddell, R. Webb","doi":"10.1109/HIS.2006.22","DOIUrl":"https://doi.org/10.1109/HIS.2006.22","url":null,"abstract":"Motivation for this research is the real-time restoration of faint astronomical images through turbulence over a large field-of-view. A simulation platform was developed to predict the centroid of a science object, convolved through multiple perturbation fields, and projected on to an image plane. Centroid data were selected from various source and target locations and used to train an artificial neural network to estimate centroids over a spatial grid, defined on the image plane. The capability of the network to learn to predict centroids over new target locations was assessed using a priori centroid data corresponding to selected grid locations. Various distortion fields were used in training and simulating the network including data collected from observation runs at a local observatory. Results from this work provide the basis for extensions and application to modal tomography.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115868882","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
Monitoring Genetic Variations in Variable Length Evolutionary Algorithms 监测变长度进化算法中的遗传变异
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.47
M. Defoin-Platel, M. Clergue
{"title":"Monitoring Genetic Variations in Variable Length Evolutionary Algorithms","authors":"M. Defoin-Platel, M. Clergue","doi":"10.1109/HIS.2006.47","DOIUrl":"https://doi.org/10.1109/HIS.2006.47","url":null,"abstract":"Initially, Artificial Evolution focuses on Evolutionary Algorithms handling solutions coded in fixed length structures. In this context, the role of crossover is clearly the mixing of information between solutions. The development of Evolutionary Algorithms operating on structures with variable length, of which genetic programming is one of the most representative instances, opens new questions on the effects of crossover. Beside mixing, two new effects are identified : the diffusion of information inside solutions and the variation of the solutions sizes. In this paper, we propose a experimental framework to study these three effects and apply it on three different crossovers for genetic programming : the Standard Crossover, the One-Point Crossover and the Maximum Homologous Crossover. Exceedingly different behaviors are reported leading us to consider the necessary future decoupling of the mixing, the diffusion and the size variation.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115998273","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
Shape Representation and Distance Measure Based on Relational Graph 基于关系图的形状表示与距离度量
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.63
Jin Tang, Chunyan Zhang, B. Luo
{"title":"Shape Representation and Distance Measure Based on Relational Graph","authors":"Jin Tang, Chunyan Zhang, B. Luo","doi":"10.1109/HIS.2006.63","DOIUrl":"https://doi.org/10.1109/HIS.2006.63","url":null,"abstract":"Nowadays, the efficient representation of a given shape plays a significant role in pattern recognition field. In this paper, we introduce a novel method to represent 2-D shape as a relation graph which using affine-invariant Fourier. This presentation method has invariance properties, such as scaling, shifting, rotation and starting point. Then edit distance is used to measure the distance between graphs. Embedding and recognition experiments are carried out to test the performance of affine-invariant Fourier based weighted graph(AFWG). Experimental results show that AFWG can preserve the shape feature well and can be applied to shape-related application.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126764006","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
Language as a Small World Network 语言作为一个小世界网络
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.39
M. Markosová, P. Nather
{"title":"Language as a Small World Network","authors":"M. Markosová, P. Nather","doi":"10.1109/HIS.2006.39","DOIUrl":"https://doi.org/10.1109/HIS.2006.39","url":null,"abstract":"Small world networks are graphs, which integrate the properties of random graphs and lattice graphs [5]. Several real networks can be modeled with a help of small worlds [1, 2, 6, 8]. As shown in this paper a word web has small world structure too. We have shown, that different languages, such as Slovak and English, have similar small world properties. As our second goal, we built a graph on the basis of kernel lexicon words, in order to test the scaling results of Cancho and Sol¿ [6]. We speculate that the differences between calculated and measured exponents of connectivity distribution are due to the node aging.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127809876","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: 7
hLCGA: A Hybrid Competitive Coevolutionary Genetic Algorithm hLCGA:混合竞争协同进化遗传算法
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.32
Grégoire Danoy, P. Bouvry, T. Martins
{"title":"hLCGA: A Hybrid Competitive Coevolutionary Genetic Algorithm","authors":"Grégoire Danoy, P. Bouvry, T. Martins","doi":"10.1109/HIS.2006.32","DOIUrl":"https://doi.org/10.1109/HIS.2006.32","url":null,"abstract":"We introduce in this article a new hybrid coevolutionary algorithm called hLCGA (hybrid Loosely Coupled Genetic Algorithm) that consists in combining a competitive coevolutionary genetic algorithm and a local search algorithm. We apply it to the Rosenbrock function optimization problem and compare the results of five hybrid variants to the original LCGA. We show the advantages of hybridizing a coevolutionary algorithm with local search algorithms in terms of solution quality and convergence speed.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127476686","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: 11
A Comparative Analysis of Data Distribution Methods in an Agent-Based Neural System for Classification Tasks 基于agent的分类任务神经系统中数据分布方法的比较分析
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.1
L. E. A. Santana, A. Canuto, J. C. Xavier, André M. C. Campos
{"title":"A Comparative Analysis of Data Distribution Methods in an Agent-Based Neural System for Classification Tasks","authors":"L. E. A. Santana, A. Canuto, J. C. Xavier, André M. C. Campos","doi":"10.1109/HIS.2006.1","DOIUrl":"https://doi.org/10.1109/HIS.2006.1","url":null,"abstract":"The NeurAge (Neural agents) system has been proposed as an alternative to transform the centralized decision making process of a multi-classifier system into a distributed, flexible and incremental one. This system has presented good results in some conventional (centralized) classification tasks. Nevertheless, in some classification tasks, relevant features might be distributed over a set of agent. These applications can be classified as distributed classification tasks. In this paper, a comparative investigation of the NeurAge system using some methods for data distribution will be performed. In addition, the performance of the NeurAge system will be compared with some existing multi-classifier systems.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116904296","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: 7
Semi-Supervised Clustering of Corner-Oriented Attributed Graphs 面向角属性图的半监督聚类
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.62
Jin Tang, Chunyan Zhang, B. Luo
{"title":"Semi-Supervised Clustering of Corner-Oriented Attributed Graphs","authors":"Jin Tang, Chunyan Zhang, B. Luo","doi":"10.1109/HIS.2006.62","DOIUrl":"https://doi.org/10.1109/HIS.2006.62","url":null,"abstract":"This paper describes a new algorithm for image semi-supervised clustering. In particular, the proposed approach introduces corner-oriented attributed graphs(COAG) constructed based on modified Harris corner extraction method to represent structure objects . 2D-Laplacianface is used to reduce the dimension of feature matrix obtained from COAG. Feature vector is built just from the output of dimensionality reduction. This vector denotes the input to the classifier. Semi-supervised k-mean clustering method (S2KMCM) is carried out as semi-clustering method. Experimental results show that COAG can preserve the structure information of image and S2KFCM can be applied to both clustering and classification tasks by labeled and unlabeled data together.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134523085","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
An Improved Adaptive Algorithm for Controlling the Probabilities of Crossover and Mutation Based on a Fuzzy Control Strategy 基于模糊控制策略的控制交叉和突变概率的改进型自适应算法
2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06) Pub Date : 2006-12-13 DOI: 10.1109/HIS.2006.12
Qing Li, X. Tong, Sijiang Xie, Guangjun Liu
{"title":"An Improved Adaptive Algorithm for Controlling the Probabilities of Crossover and Mutation Based on a Fuzzy Control Strategy","authors":"Qing Li, X. Tong, Sijiang Xie, Guangjun Liu","doi":"10.1109/HIS.2006.12","DOIUrl":"https://doi.org/10.1109/HIS.2006.12","url":null,"abstract":"An improved adaptive algorithm for controlling the probabilities of crossover and mutation with fuzzy logic is proposed in this paper. The changes of average fitness value and standard deviation between two continuous generations are selected as input and the changes of crossover probability and mutation probability are the output variables. Two adaptive scaling factors are introduced for normalizing the input variables and new fuzzy rules based on domain heuristic knowledge are investigated for adjusting the probabilities of crossover and mutation. Numerical simulation studies of three different test functions are carried out, and the simulation results show that the genetic algorithm with the proposed adaptive fuzzy controller exhibits improved search speed and quality.","PeriodicalId":150732,"journal":{"name":"2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133070758","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: 16
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