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2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)最新文献

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Support vector machine based on Genetic Algorithm integrated navigation fault detection parameter optimization method 基于遗传算法的支持向量机集成导航故障检测参数优化方法
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967741
Huaijian Li, Jing Fang, Xiaojing Du, Ziye Hu
{"title":"Support vector machine based on Genetic Algorithm integrated navigation fault detection parameter optimization method","authors":"Huaijian Li, Jing Fang, Xiaojing Du, Ziye Hu","doi":"10.1109/DOCS55193.2022.9967741","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967741","url":null,"abstract":"In order to solve the problem of low fault detection rate of combinatorial navigation due to the mismatch of support vector machine parameters, this paper uses genetic algorithm and lattice search method to find the optimal support vector machine penalty parameter C and kernel function parameter g. The result of the search is brought into the support vector machine to obtain the classification model and finally classify the combinatorial navigation data. The results show that the genetic algorithm has a faster search speed and a higher classification accuracy.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126134634","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
Review of Improved Cooperative Control of Unmanned Surface Vehicle Based on Multi-Agent System 基于多智能体系统的改进无人水面车辆协同控制研究综述
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967730
Wei Liu, Qihe Shan, Yuhao Mao, Jingchen Wang
{"title":"Review of Improved Cooperative Control of Unmanned Surface Vehicle Based on Multi-Agent System","authors":"Wei Liu, Qihe Shan, Yuhao Mao, Jingchen Wang","doi":"10.1109/DOCS55193.2022.9967730","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967730","url":null,"abstract":"This paper introduces the development of unmanned surface vehicle (USV) and the development of multi-USV cluster cooperative control in recent years, including the research progress of USV technology in several major countries and the research status of multi-USV cluster cooperative control. From the aspect of communication technology, the commonly used communication methods for multi-USV cluster cooperative control are introduced, and several key transmission technologies in maritime wireless communication systems are listed. Based on multi-agent theory, several types of multi-USV cluster cooperative distributed control methods are introduced, including formation control, path tracking, and containment control.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115121149","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
Graph Attention Memory for Visual Navigation 视觉导航的注意记忆图
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2019-05-11 DOI: 10.1109/DOCS55193.2022.9967733
Dong Li, Dongbin Zhao, Qichao Zhang, Yuzheng Zhuang, Bin Wang
{"title":"Graph Attention Memory for Visual Navigation","authors":"Dong Li, Dongbin Zhao, Qichao Zhang, Yuzheng Zhuang, Bin Wang","doi":"10.1109/DOCS55193.2022.9967733","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967733","url":null,"abstract":"Visual navigation in complex environments is inefficient with traditional reactive policy or general-purposed recurrent policy due to the long-term memory problem. To address this issue, this paper proposes a graph attention memory (GAM) architecture consisting of memory construction module, graph attention module, and control module. The memory construction module builds the topological graph based on supervised learning by taking the exploration prior. Then, guided attention features to reach the goal are extracted with the graph attention module. Finally, the deep reinforcement learning based control module makes decisions based on visual observations and guided attention features. In addition, the convergence of the proposed GAM module for recurrent attention operation is analyzed in this paper. We evaluate GAM-based navigation system in two complex 3D ViZDoom environments. Experimental results show that the GAM-based navigation system outperforms all baselines in both success rate and navigation efficiency, and significantly improves the generalization.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126444840","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: 10
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