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2009 Fifth International Conference on Natural Computation最新文献

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Computation of the Schroedinger Equation via the Discrete Derivatives Representation Method: Improvement of Solutions Using Particle Swarm Optimization 用离散导数表示法计算薛定谔方程:用粒子群优化改进解
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.17
A. Zerarka, H. Saidi, N. Khelil
{"title":"Computation of the Schroedinger Equation via the Discrete Derivatives Representation Method: Improvement of Solutions Using Particle Swarm Optimization","authors":"A. Zerarka, H. Saidi, N. Khelil","doi":"10.1109/ICNC.2009.17","DOIUrl":"https://doi.org/10.1109/ICNC.2009.17","url":null,"abstract":"We develop the discrete derivatives representation method(DDR) to find the physical structures of the Schrodinger equation in which the interpolation polynomial of Bernstein has been used. In this paper the particle swarm optimization (PSO for short) has been suggested as a means to improve qualitatively the solutions. This approach is carefully handled and tested with a numerical example.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122275255","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
Evolving Cellular Automata - Based Flexible Job Shop Scheduling 基于元胞自动机的柔性作业车间调度
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.794
T. Witkowski, A. Antczak, Soliman Elzway, P. Antczak
{"title":"Evolving Cellular Automata - Based Flexible Job Shop Scheduling","authors":"T. Witkowski, A. Antczak, Soliman Elzway, P. Antczak","doi":"10.1109/ICNC.2009.794","DOIUrl":"https://doi.org/10.1109/ICNC.2009.794","url":null,"abstract":"The paper presents evolving cellular automata-based scheduling production. The models have been implemented and tested, and the examples have been illustrated. The software of this model, allows us to analyze the process of construction schedule for many variants reflecting a variety of combinations other factors. The results indicate that the proposed algorithm is an efficient approach to solve FJSP.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132115906","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
Immune System Multiobjective Optimization Algorithm for DTLZ Problems DTLZ问题的免疫系统多目标优化算法
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.135
Bin Zhang, Weihua Ren, Lihua Zhao, Xiaozheng Deng
{"title":"Immune System Multiobjective Optimization Algorithm for DTLZ Problems","authors":"Bin Zhang, Weihua Ren, Lihua Zhao, Xiaozheng Deng","doi":"10.1109/ICNC.2009.135","DOIUrl":"https://doi.org/10.1109/ICNC.2009.135","url":null,"abstract":"Based on Artificial Immune System, a novel Immune System Multiobjective Optimization Algorithm (ISMOA) is proposed. ISMOA presents nondominated sorting clonal selection operation, preserving the diversity of the population and more uniformly distributing global Pareto optimal solutions. The comparisons of ISMOA with NSGAII in DTLZ problems suggest that ISMOA clearly outperforms in converging towards the true front coverage and finding the spread of solutions.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130157061","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: 4
The Comparative Research of Solving Multi-task Scheduling Problems with GA and PSO 遗传算法与粒子群算法求解多任务调度问题的比较研究
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.206
Tian-jiao Zhang, Wen-lan Fan, Yanli Li
{"title":"The Comparative Research of Solving Multi-task Scheduling Problems with GA and PSO","authors":"Tian-jiao Zhang, Wen-lan Fan, Yanli Li","doi":"10.1109/ICNC.2009.206","DOIUrl":"https://doi.org/10.1109/ICNC.2009.206","url":null,"abstract":"Genetic algorithm and particle swarm optimization both belong to the evolutionary algorithms; they have much in common, but also have some differences. The paper set out from Multi-task scheduling problem, discussed in detail the method of utilizing GA and PSO to equilibrium and optimize Multi-task scheduling problem under the constraints of resources separately. Through the analysis of comparative experiment, two kinds of intelligence-optimizing methods made very good results when solved a same problem, but in most cases, PSO had a faster rate of convergence than GA, but GA had a better convergent result than PSO.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130258114","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
A New Evolutionary Algorithm for Solving Multiobjective Optimization 求解多目标优化问题的一种新的进化算法
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.199
Yang Song, Junzhong Ji, Yamin Wang, Chunnian Liu
{"title":"A New Evolutionary Algorithm for Solving Multiobjective Optimization","authors":"Yang Song, Junzhong Ji, Yamin Wang, Chunnian Liu","doi":"10.1109/ICNC.2009.199","DOIUrl":"https://doi.org/10.1109/ICNC.2009.199","url":null,"abstract":"Evolutionary Algorithm (EA) is a population-based metaheuristic technique to effectively solve Multiobjective Optimization Problem (MOP). However, it is still an active research topic how to improve the performance of MOEA algorithms. In this paper, we present a new FOPF algorithm,which can alleviate MOEA’s disadvantage on time performance. First, a fast obtaining Pareto front approach with less computation cost is proposed, then an expand approach and a limited crossover procedure are employed to keep the diversity of solutions. Experimental results on four test problems show that the FOPF algorithm is able to find solutions with good diversity, which are near the true Parato-optimal front, and improves significantly time performance compared to the known NSGA2.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130479639","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
StSUT2 Structure Prediction Based on Nucleic Acid Sequence Using GA-BP 基于GA-BP核酸序列的StSUT2结构预测
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.172
Zhengwei Zhu, Yuying Guo
{"title":"StSUT2 Structure Prediction Based on Nucleic Acid Sequence Using GA-BP","authors":"Zhengwei Zhu, Yuying Guo","doi":"10.1109/ICNC.2009.172","DOIUrl":"https://doi.org/10.1109/ICNC.2009.172","url":null,"abstract":"The protein secondary structure (PSS) prediction system presented in this paper is a subsystem of potato bioinformation research platform. The proposed method is a novel and practical PSS prediction method, which is based on nucleic acid sequence (NAS), uses an combined neural network (CNN) and takes an improved genetic algorithm (GA) to optimize the connection weights of CNN. The experimental results indicate that, not only the proposed method is feasible, but compared with the traditional PSS prediction methods, its prediction accuracy is higher, its use is more convenient, its search speed is faster and it has confidentiality in a certain degree.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133896246","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
Vehicle Routing Problem with Time Windows: A Hybrid Particle Swarm Optimization Approach 带时间窗的车辆路径问题:一种混合粒子群优化方法
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.353
Xiaoxiang Liu, Weigang Jiang, Jianwen Xie
{"title":"Vehicle Routing Problem with Time Windows: A Hybrid Particle Swarm Optimization Approach","authors":"Xiaoxiang Liu, Weigang Jiang, Jianwen Xie","doi":"10.1109/ICNC.2009.353","DOIUrl":"https://doi.org/10.1109/ICNC.2009.353","url":null,"abstract":"Vehicle routing problem (VRP) is a well-known combinatorial optimization and nonlinear programming problem seeking to service a number of customers with a fleet of vehicles. This paper proposes a hybrid particle swarm optimization (HPSO) algorithm for VRP. The proposed algorithm utilizes the crossover operation that originally appears in genetic algorithm (GA) to make its manipulation more readily and avoid being trapped in local optimum, and simultaneously for improving the convergence speed of the algorithm, level set theory is also added to it. We employ the HPSO algorithm to an example of VRP, and compare its result with those generated by PSO, GA, and parallel PSO algorithms. The experimental comparison results indicate that the performance of HPSO algorithm is superior to others, and it will become an effective approach for solving discrete combinatory problems.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134386944","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: 13
Objective Reduction Based on the Least Square Method for Large-Dimensional Multi-objective Optimization Problem 基于最小二乘法的大维多目标优化问题目标约简
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.40
Cong Zhou, Jinhua Zheng, Ke Li, Huixiang Lv
{"title":"Objective Reduction Based on the Least Square Method for Large-Dimensional Multi-objective Optimization Problem","authors":"Cong Zhou, Jinhua Zheng, Ke Li, Huixiang Lv","doi":"10.1109/ICNC.2009.40","DOIUrl":"https://doi.org/10.1109/ICNC.2009.40","url":null,"abstract":"In the real-world applications, many multi-objective optimization involve a large number of objective, however, existing evolutionary multi-objective optimization algorithms are applied only to a few number of objective. Because of inconvenience in handling large number of objective, researchers start to deal with how to reduce the redundant objectives. In this paper, we firstly introduce some existing algorithms on transforming high-dimensional to low-dimensional, and then propose a new algorithm, namely large dimensionality reduction based on the least square method. This method fits every objective function to a line, and compares the slope differences between each two lines, finally makes certain which one is redundancy and further reduces this one. This experiment shows, on one hand, there are some redundant objective functions in certain large dimensionality multi-objective optimization problems, and the objective space of non-redundant objective function is accordant with the low-dimensional true Pareto front. On other hand, the experiment result with other similar algorithm shows our algorithm is competitive and the efficacy of the procedure is demonstrated.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131499866","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: 12
On Object Perception in Enhanced Reality Environment for Robot Telecontrol 机器人遥控增强现实环境中的物体感知研究
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.13
Chensheng Wang, Fei Wang, T. Wiegers
{"title":"On Object Perception in Enhanced Reality Environment for Robot Telecontrol","authors":"Chensheng Wang, Fei Wang, T. Wiegers","doi":"10.1109/ICNC.2009.13","DOIUrl":"https://doi.org/10.1109/ICNC.2009.13","url":null,"abstract":"Object recognition is one of the hot topics in computer vision. Existing techniques for object recognition are based on image processing, which tends to be incapable to recover the topological information of the object. In this paper, based on the analysis of human perceptual habit, a novel strategy for object recognition is proposed. The method perceives an object in the scene by means of existing shape knowledge coupling. And a mechanism is designed to grow the system intelligence by depositing the shape knowledge into a repository once a new object is encountered. This makes the system be in a constant way to become more and more intelligent. In addition, the proposed strategy is advantageous in rebuilding the whole object information with the support of the repository. Experiment results carried out in the enhanced reality environment for robot telecontrol shows that the proposed strategy is both valid and effective for the designed application.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131889108","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
Improved Neural Efficiency under Matching Condition for Gifted Children 资优儿童匹配条件下神经效率的提高
2009 Fifth International Conference on Natural Computation Pub Date : 2009-08-14 DOI: 10.1109/ICNC.2009.219
Xiaoju Duan, Jiannong Shi, Jianhui Wu
{"title":"Improved Neural Efficiency under Matching Condition for Gifted Children","authors":"Xiaoju Duan, Jiannong Shi, Jianhui Wu","doi":"10.1109/ICNC.2009.219","DOIUrl":"https://doi.org/10.1109/ICNC.2009.219","url":null,"abstract":"To investigate the neural efficiency theory of intelligence, electroencephalograms (EEG) were recorded while 15 intellectually gifted children and 15 average children performed a 2-back working memory task. The amplitude of P2, N2, and LPC were analyzed. The results showed that intellectually gifted children performed more accurately and had larger LPC mean amplitudes than their intellectually average peers under the matching condition, suggesting that intellectually gifted individual can use their brain and allocate cognitive resources more efficiently.","PeriodicalId":235382,"journal":{"name":"2009 Fifth International Conference on Natural Computation","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132909134","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
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