{"title":"Facial feature extraction using genetic algorithm","authors":"G. Yen, Nethrie Nithianandan","doi":"10.1109/CEC.2002.1004532","DOIUrl":"https://doi.org/10.1109/CEC.2002.1004532","url":null,"abstract":"An automatic facial feature extraction method is presented in this paper. The method is based on the edge density distribution of the image. In the preprocessing stage a face is approximated to an ellipse, and a genetic algorithm is applied to search for the best ellipse region match. In the feature extraction stage, the genetic algorithm is applied to extract the facial features, such as the eyes, nose and mouth, in the predefined sub regions. The simulation results validates that the proposed method is capable of automatically extracting features from various video images effectively under natural lighting environments and in the presence of certain amount of artificial noise and of multi-face oriented with angles.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128668652","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}
Liu Xin, P. Vadakkepat, Tong-heng Lee, X. Peng, Pang Ki Kim
{"title":"Comparison of Khepera robot navigation by evolutionary neural networks and pain-based algorithm","authors":"Liu Xin, P. Vadakkepat, Tong-heng Lee, X. Peng, Pang Ki Kim","doi":"10.1109/CEC.2002.1004549","DOIUrl":"https://doi.org/10.1109/CEC.2002.1004549","url":null,"abstract":"A comparison of mobile robot navigation using evolutionary neural networks and the pain based algorithm is discussed in this paper. The controllers are designed based on evolutionary neural networks and the pain-based algorithms. The performance of the controllers are verified with the Khepera robot.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127140281","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}
P. Hingston, Edith Cowan, L. Barone, Evolving Crushers, P. Hingston
{"title":"Evolving crushers","authors":"P. Hingston, Edith Cowan, L. Barone, Evolving Crushers, P. Hingston","doi":"10.1109/CEC.2002.1004398","DOIUrl":"https://doi.org/10.1109/CEC.2002.1004398","url":null,"abstract":"This paper describes the use of an evolutionary algorithm to solve an engineering design problem. The problem involves determining the geometry and operating settings for a crusher in a comminution circuit for ore processing. The intention is to provide a tool for consulting engineers that can be used to explore candidate designs for various scenarios. The algorithm has proved capable of deriving designs that are clearly superior to existing designs, promising significant financial benefits.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127275236","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":"Agent-based models as a complement to economic theory: a durable goods example","authors":"Troy Tassier, M. Everson, D. Ostrowski","doi":"10.1109/CEC.2002.1007016","DOIUrl":"https://doi.org/10.1109/CEC.2002.1007016","url":null,"abstract":"We construct an agent-based model of a durable goods market. Consumer purchasing strategies include memory of recent price realizations in the market. A monopolistic producer sets prices using a standard economic approach. The model yields aggregate market characteristics similar to those seen in automobile markets.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127242249","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":"Threshold selection, hypothesis tests, and DOE methods","authors":"T. Bartz-Beielstein, S. Markon","doi":"10.1109/CEC.2002.1007024","DOIUrl":"https://doi.org/10.1109/CEC.2002.1007024","url":null,"abstract":"Threshold selection-a selection mechanism for noisy evolutionary algorithms-is put into the broader context of hypothesis testing. Optimal selection thresholds were derived theoretically. These theoretical results were used to find threshold values for a simple model of stochastic search and for a simplified elevator simulator. Design of experiments methods are used to validate the significance of the results.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126965673","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 coordination mechanism for real world scheduling problems using genetic algorithms","authors":"A. Madureira, C. Ramos, S. Silva","doi":"10.1109/CEC.2002.1006229","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006229","url":null,"abstract":"This paper starts by presenting a scheduling framework, based on genetic algorithms for the resolution of real world scheduling problems, which considers job release times, job due dates and different assembly levels. This framework is based on a decomposition of the job-shop scheduling problem into a series of deterministic single machine scheduling problem. A coordination mechanism is proposed.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129257637","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":"Evolving 3D model interpretation of images using graphics hardware","authors":"Frederik Lindblad, P. Nordin, Krister Wolff","doi":"10.1109/CEC.2002.1006238","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006238","url":null,"abstract":"We present a novel approach for 3D-scene interpretation with numerous applications, for instance in robotics. The models are rendered using 3d graphics hardware and DirectX. Both artificial and real images were used to test the system. More than one target image can be used, allowing stereoscopic vision. These experiments present results of interesting generalization.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125356697","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":"Asynchronous self-adjustable island genetic algorithm for multi-objective optimization problems","authors":"Zhong-Yao Zhu, K. Leung","doi":"10.1109/CEC.2002.1007034","DOIUrl":"https://doi.org/10.1109/CEC.2002.1007034","url":null,"abstract":"In this paper, we present a new algorithm-asynchronous self-adjustable island genetic algorithm (aSAIGA) for multi-objective optimization problems. The proposed algorithm is built upon the coarse-grained architecture, which is divided into sub-processes and distributed amongst several island processors. In each sub-process, an asynchronous communication operation and a self-adjusting operation are adopted to enhance the algorithm in both speedup and global searching capabilities. Satisfactory results and significant speedup can be achieved by aSAIGA, as shown by simulation.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125511642","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 scalable and robust framework for distributed applications","authors":"Márk Jelasity, Mike Press, B. Paechter","doi":"10.1109/CEC.2002.1004471","DOIUrl":"https://doi.org/10.1109/CEC.2002.1004471","url":null,"abstract":"This paper describes a novel tool for running distributed experiments on the Internet. The possible applications include simple load balancing, parallel evolutionary computation, agent-based simulation and artificial life. Our environment is based on cutting-edge peer-to-peer (P2P) technology. We demonstrate the potentials of the framework by analyzing a simple distributed multistart hillclimber application. We present theoretical and empirical evidence that our approach is scalable, effective and robust.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"385 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122988818","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":"Adaptive denoising in spectral analysis by genetic programming","authors":"J. Rowland, Janet Taylor","doi":"10.1109/CEC.2002.1006222","DOIUrl":"https://doi.org/10.1109/CEC.2002.1006222","url":null,"abstract":"This paper relates to supervised interpretation of the infrared analytical spectra of complex biological samples. The aim is to produce a model that can predict the value of a measurand of interest, such as the concentration of a particular chemical constituent in complex biological material. Conventionally, a number of spectra are co-added to reduce measurement noise and this is time consuming. In this paper we demonstrate the ability of evolutionary search to provide adaptive averaging of spectral regions to provide selective tradeoff between spectral resolution and signal-to-noise ratio. The resultant denoised subset of the variables is then input to a proprietary Genetic Programming (GP) package which forms a predictive model that compares well in predictive power with a combination of Partial Least Squares Regression (PLS) and adaptive denoising. This demonstrates the considerable advantage that, given appropriate node functions, the GP could handle the entire process of denoising and forming the final predictive model all in one stage. This reduces or removes the need for co-adding with a consequent reduction in data acquisition time.","PeriodicalId":184547,"journal":{"name":"Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600)","volume":"35 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2002-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120902513","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}