2008 IEEE Swarm Intelligence Symposium最新文献_第2页

An Ant Colony Optimization using training data applied to UAV way point path planning in wind 基于训练数据的蚁群算法在无人机航路点路径规划中的应用

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668302

A. Jennings, R. Ordóñez, N. Ceccarelli

引用次数: 16

Cautious particle swarm 谨慎的粒子群

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668292

Hiroshi Someya

引用次数: 5

Optimal pheromone distribution for ANCOR ANCOR的最佳信息素分布

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668311

Deniz Demiray, D. Altilar

引用次数: 0

An evaluation of two swarm intelligence MANET routing algorithms in an urban environment 城市环境下两种群智能MANET路由算法的评价

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668322

F. Ducatelle, G. D. Caro, L. Gambardella

{"title":"An evaluation of two swarm intelligence MANET routing algorithms in an urban environment","authors":"F. Ducatelle, G. D. Caro, L. Gambardella","doi":"10.1109/SIS.2008.4668322","DOIUrl":"https://doi.org/10.1109/SIS.2008.4668322","url":null,"abstract":"We study through simulation the performance of two swarm intelligence MANET routing algorithms in a realistic urban environment. The two algorithms, ANSI and AntHocNet, implement the swarm intelligence paradigm for routing in different ways: while ANSI applies a reactive approach in which ants are only sent out when no route is available between the source and destination of a communication session, AntHocNet integrates reactive and proactive mechanisms whereby the algorithm sends out ants at regular intervals during the entire duration of running sessions in order to continuously adapt and improve existing routes. The two swarm intelligence routing algorithms are compared to AODV, a state-of-the-art reactive algorithm, and OLSR, a state-of-the-art proactive algorithm. Our objective is to investigate the usefulness of the different approaches adopted by the algorithms when confronted with the peculiarities of urban environments and the requirements of real-world applications. At this aim we define a detailed and realistic simulation setup. We model node mobility by limiting node movements to the streets and open spaces of town, use a ray-tracing approach to model the propagation of radio waves, and investigate different kinds of interactive data traffic patterns, ranging from SMS messaging to VoIP communications.","PeriodicalId":178251,"journal":{"name":"2008 IEEE Swarm Intelligence Symposium","volume":"435 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125802665","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: 15

Meta-heuristic cross-layer protocol for UWB emergency responder sensor network 超宽带应急响应传感器网络的元启发式跨层协议

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668325

R. Muraleedharan, Weihua Gao, L. Osadciw

引用次数: 3

Agents based algorithms for design parameter estimation in contaminant transport inverse problems 基于agent的污染物输运逆问题设计参数估计算法

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668312

T. V. Bharat

{"title":"Agents based algorithms for design parameter estimation in contaminant transport inverse problems","authors":"T. V. Bharat","doi":"10.1109/SIS.2008.4668312","DOIUrl":"https://doi.org/10.1109/SIS.2008.4668312","url":null,"abstract":"A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigenvalues obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigenvalues from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigenvalues are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.","PeriodicalId":178251,"journal":{"name":"2008 IEEE Swarm Intelligence Symposium","volume":"168 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133848632","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: 9

Balancing transmission power and hop count in ad hoc unicast routing with swarm intelligence 基于群智能的自组织单播路由中传输功率和跳数的平衡

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668323

Ke Li, Chien-Chung Shen

引用次数: 0

A study of Particle Swarm Optimization on leukocyte adhesion molecules and control strategies for smart prosthetic hand 智能假手白细胞粘附分子的粒子群优化及控制策略研究

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668324

Cheng-Hung Chen, K. Bosworth, M. Schoen, S. Bearden, D. Naidu, A. P. Gracia

引用次数: 9

Surrogate-based Multi-Objective Particle Swarm Optimization 基于代理的多目标粒子群优化

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668300

Luis V. Santana-Quintero, C. Coello, A. G. Hernández-Díaz, J. Velázquez-Reyes

{"title":"Surrogate-based Multi-Objective Particle Swarm Optimization","authors":"Luis V. Santana-Quintero, C. Coello, A. G. Hernández-Díaz, J. Velázquez-Reyes","doi":"10.1109/SIS.2008.4668300","DOIUrl":"https://doi.org/10.1109/SIS.2008.4668300","url":null,"abstract":"This paper presents a new algorithm that approximates real function evaluations using supervised learning with a surrogate method called support vector machine (SVM). We perform a comparative study among different leader selection schemes in a multi-objective particle swarm optimizer (MOPSO), in order to determine the most appropriate approach to be adopted for solving the sort of problems of our interest. The resulting hybrid presents a poor spread of solutions, which motivates the introduction of a second phase to our algorithm, in which an approach called rough sets is adopted in order to improve the spread of solutions along the Pareto front. Rough sets are used as a local search engine, which is able to generate solutions in the neighborhood of the nondominated solutions previously generated by the surrogate-based algorithm. The resulting approach is able to generate reasonably good approximations of the Pareto front of problems of up to 30 decision variables with only 2,000 fitness function evaluations. Our results are compared with respect to the NSGA-II, which is a multi-objective evolutionary algorithm representative of the state-of-the-art in the area.","PeriodicalId":178251,"journal":{"name":"2008 IEEE Swarm Intelligence Symposium","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133489257","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: 8

Image-based tracking with Particle Swarms and Probabilistic Data Association 基于粒子群和概率数据关联的图像跟踪

2008 IEEE Swarm Intelligence Symposium Pub Date : 2008-11-07 DOI: 10.1109/SIS.2008.4668297

E. Kao, Peter VanMaasdam, John W. Sheppard

引用次数: 4