{"title":"Comparisons between heuristics based on correlativity and efficiency for landmarker generation","authors":"Daren Ler, I. Koprinska, S. Chawla","doi":"10.1109/ICHIS.2004.33","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.33","url":null,"abstract":"Recently, we proposed a new meta-learning approach based on landmarking. This approach, which utilises a new set of criteria for selecting landmarkers, generates a set of landmarkers that are each functions over the performance over subsets of the candidate algorithms being landmarked. In this paper, we experiment with three heuristics based on correlativity and efficiency. With each heuristic, the landmarkers generated using linear regression are able to estimate accuracy well, even when only utilising a small fraction of the given algorithms. The results also show that the heuristic in which efficiencies are estimated via 1-nearest neighbour outperformed the other heuristics.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123282243","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":"A fuzzy clustering algorithm using cellular learning automata based evolutionary algorithm","authors":"R. Rastegar, A. Arasteh, A. Hariri, M. Meybodi","doi":"10.1109/ICHIS.2004.3","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.3","url":null,"abstract":"In this paper, a new fuzzy clustering algorithm that uses cellular learning automata based evolutionary computing (CLA-EC) is proposed. The CLA-EC is a model obtained by combining the concepts of cellular learning automata and evolutionary algorithms. The CLA-EC is used to search for cluster centers in such a way that minimizes the clustering criterion. The simulation results indicate that the proposed algorithm produces clusters with acceptable quality with respect to clustering criterion and provides a performance that is superior to that of the C-means algorithm.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127620613","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 clustering with a regularized autoassociative neural network","authors":"Alejandro Bassi, J. D. Velásquez, H. Yasuda","doi":"10.1109/ICHIS.2004.47","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.47","url":null,"abstract":"We propose a fuzzy clustering method that relies on an artificial neural network scheme based on an encoder-decoder architecture with autoassociative training. The encoder is designed to implement a set of competing fuzzy membership functions which are trained to fit the data so that the decoder reconstruction error is minimized. In order to enforce a suitable cluster partitioning and membership distribution, the critical factor of the method is an entropy based regularization that constrains the encoder outputs. We present the results of our approach applied to synthetic data sets featuring both disjoin and intersecting compact clusters.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122708957","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}
T. Tateyama, Z. Nakao, Xiang-Yan Zeng, Yenwei Chen
{"title":"Segmentation of high resolution satellite images by direction and morphological filters","authors":"T. Tateyama, Z. Nakao, Xiang-Yan Zeng, Yenwei Chen","doi":"10.1109/ICHIS.2004.85","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.85","url":null,"abstract":"This paper examines images taken from IKONOS to extract several features such as road relations automatically. We propose a new method which combines color, texture information and shape information for segmentation of high resolution satellite images. The method uses color and texture information for global segmentation, and shape information for local analysis. We propose a new direction filter which pays its attention to road features having information on specific directionality. We also propose another new morphology filter which is used as a length filter extracting length of each region more efficiently.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123444388","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":"Image clustering system on WWW using Web texts","authors":"W. Sunayama, Akiko Nagata, M. Yachida","doi":"10.1109/ICHIS.2004.59","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.59","url":null,"abstract":"As the Internet becomes the basic resource of information, not only texts but image retrieval systems have appeared. However, many supply only a list of images, so we must seek desired images one by one. Image labeling is one solution to such a problem, in which various words are labeled to an image when extracted from a single Web page. Therefore, this paper proposes an image clustering system that labels images by words related to a search keyword. Relationships are measured by Web pages in WWW. In experiments, users found the intended images faster than ordinary image search system.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122169900","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":"Innate and acquired immunity in real time systems","authors":"Dan W. Taylor, D. Corne","doi":"10.1109/ICHIS.2004.62","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.62","url":null,"abstract":"In most potential industrial applications of artificial immune systems for early fault detection, some form of simple fault detection system already exists. We propose that this existing layer of simple, generally rule-based fault detection is analogous to innate immunity in the natural immune system. We argue that the artificial acquired immune system should focus on the detection of fault conditions not already covered by the innate immune system, most importantly on the very early symptoms of faults which, we believe, are often very similar to self. This has implications for detector generation algorithms. We test two novel detector generation algorithms that address this issue, using temperature data from refrigerated cabinets in UK supermarkets. Results show that location of detectors in problem space is important and that detector sets concentrated close to self in problem space are better at detecting early stages of fault.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114746594","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":"A novel adaptive decision making agent architecture inspired by human behavior and brain study models","authors":"L. K. Wickramasinghe, D. Alahakoon","doi":"10.1109/ICHIS.2004.10","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.10","url":null,"abstract":"Intelligent agent technology, which expects to combine the marked trends in history of computing such as ubiquity, interconnection, intelligence, delegation and human orientation can be considered as a step towards the next stage of artificial intelligence. This new technology attempts to reduce the gap between man and machine. The remarkable ability of a human being to make decisions is art ongoing learning and evolutionary process. Therefore, when reducing the man-machine gap, one of the main issues to address is how to make agents decision makers in a human oriented way. The paper presents novel conceptual agent framework to provide human like decisions inspired by human behavior and brain study models. The proposed learning and evolutionary agent architecture make the agent capable of handling the dynamism in the environment too. The experiments illustrated with the banking application demonstrate how the proposed framework enables a software agent to make decisions in a human oriented manner.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127389248","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":"A new hybrid methodology for intelligent Chinese character recognition","authors":"D. Al-Dabass, David J. Evans, M. Ren","doi":"10.1109/ICHIS.2004.8","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.8","url":null,"abstract":"A new methodology is proposed to combine fuzzy possibilistic reasoning with knowledge mining of syntax dynamics using hybrid recurrent nets. The structure of Chinese characters consists of a 3-layer hierarchy of character, radical and stroke. Fuzzy possibilistic reasoning is an appropriate set of algorithmic tools to aid automatic recognition of these characters. Associative memory artificial neural network algorithms form a suitable technique for realising these concepts. Several issues are explored: vagueness of radicals, their situation, position invariance, extraction order and shape. Hybrid recurrent nets are proposed to deal with recognition at the syntax level. Each character is the 2D output of a syntax generating system, which is subjected to a knowledge mining process to determine its behaviour parameters. The knowledge mining architecture consists of an extensible recurrent hybrid net hierarchy of multiagents where the composite behaviour of agents at any one level is determined by those of the level immediately below.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122305833","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":"HDGSOM: a modified growing self-organizing map for high dimensional data clustering","authors":"R. Amarasiri, D. Alahakoon, K. Smith‐Miles","doi":"10.1109/ICHIS.2004.52","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.52","url":null,"abstract":"The growing self organizing map (GSOM) algorithm is a variant of the self organizing map (SOM). It has a dynamically growing structure that adapts to the natural structure of the data. It has been identified that the growing of the GSOM can get negatively affected when used with very large dimensional data such as those in text and DNA data sets. This paper addresses these issues and presents a modified version of the GSOM called the high dimensional GSOM (HDGSOM). The algorithm and experimental results showing the improved performance of the HDGSOM are also presented.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116126429","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":"Hierarchical tournament selection genetic algorithm for the vehicle routing problem with time windows","authors":"G. B. Alvarenga, G. Mateus","doi":"10.1109/ICHIS.2004.53","DOIUrl":"https://doi.org/10.1109/ICHIS.2004.53","url":null,"abstract":"The vehicle routing problem with time windows (VRPTW) is a well-known and complex combinatorial problem, which has received considerable attention in recent years. The VRPTW benchmark problems of Solomon (1987) have been most commonly chosen to evaluate and compare all exact and heuristic algorithms. A genetic algorithm and a set partitioning two phases approach has obtained competitive results in terms of total travel distance minimization. However, a great number of heuristics has used the number of vehicles as the first objective and travel distance as the second, subject to the first. This paper proposes a three phases approach considering both objectives. Initially, a hierarchical tournament selection genetic algorithm is applied. It can reach all best results in number of vehicles of the 56 Solomon's problems explored in the literature. After then, the two phase approach, the genetic and the set partitioning, is applied to minimize the travel distance as the second objective.","PeriodicalId":274073,"journal":{"name":"Fourth International Conference on Hybrid Intelligent Systems (HIS'04)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2004-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131347738","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}