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

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Application of Image Recognition for On-board Sailor Behavior Based on Broad Learning System 基于广义学习系统的舰上水手行为图像识别应用
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967770
Wenting Liu, Y. Zuo, Tieshan Li, C. Chen
{"title":"Application of Image Recognition for On-board Sailor Behavior Based on Broad Learning System","authors":"Wenting Liu, Y. Zuo, Tieshan Li, C. Chen","doi":"10.1109/DOCS55193.2022.9967770","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967770","url":null,"abstract":"Based on broad learning system (BLS), this paper monitors and identifies the behavior of crew members on ships. The main recognition scenarios include both of on deck and in the cabin, and the main recognition tasks include crew tracking and identification. In this paper, the video data is divided into frames and images are segmented. In the preprocessing of images, the filter is used to enhance the information and reduce the noise of the images. Finally, the recognition model is established by the BLS. In the experiment, we use BP neural network (BPNN) and support vector machine (SVM) as comparisons. The proposed method in this paper has achieved the best results in terms of recognition accuracy and training time.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"13 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":"133015380","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
A Multiobjective Evolutionary Multitasking Algorithm Based on Decomposition and Multiple Knowledge Transfer 基于分解和多重知识转移的多目标进化多任务算法
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967727
Zhongjian Wu, Qingling Zhu, Jianyong Chen
{"title":"A Multiobjective Evolutionary Multitasking Algorithm Based on Decomposition and Multiple Knowledge Transfer","authors":"Zhongjian Wu, Qingling Zhu, Jianyong Chen","doi":"10.1109/DOCS55193.2022.9967727","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967727","url":null,"abstract":"Multiobjective evolutionary multitasking (MOEMT) has become very popular in recent years, as this kind of methods aims to solve a set of multiobjective optimization problems (MOPs) simultaneously, which has been validated to be more promising than the traditional way that solves MOPs separately. However, most existing studies of MOEMT solve the MOP as a whole and use one single knowledge transfer strategy for solving all tasks, which is not so efficient as the MOP could be further decomposed into a set of subproblems and needs different strategies for knowledge transfer. To solve this problem, this paper suggests a new MOEMT algorithm (MOEMTA) based on decomposition and multiple knowledge transfer (MOEMTA-DM). First, the decomposition method is used to transform an MOP in each task into a set of subproblems, and the subproblems with greater performance improvement are chosen. Then their associated solutions will be selected to run multiple knowledge transfer strategies via both implicit and explicit ways, which can share the useful search experience between tasks. This way, computational resources can be adaptively assigned to speed up the solving of all tasks and the effect of knowledge transfer among all tasks can be improved. The effectiveness of the proposed algorithm was verified by studying benchmark multitasking MOPs (MTMOPs). Experimental results showed the proposed algorithm is more effective than other compared MOEMT algorithms.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"6 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114127892","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
Dynamic Economic Dispatch of Thermal-Wind-Storage Systems Based on Reinforcement Learning 基于强化学习的蓄热系统动态经济调度
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967708
Yuheng Li, Chengfang Hu, Junjie Fu, Shuai Wang
{"title":"Dynamic Economic Dispatch of Thermal-Wind-Storage Systems Based on Reinforcement Learning","authors":"Yuheng Li, Chengfang Hu, Junjie Fu, Shuai Wang","doi":"10.1109/DOCS55193.2022.9967708","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967708","url":null,"abstract":"This paper studies a dynamic economic dispatch (DED) problem which includes thermal and wind-storage hybrid units, aiming at minimizing the total generation cost and penalty costs involving generation regulation, load shedding, and wind curtailment. Each unit is assigned with a fixed, discrete, constrained virtual action set, and its cost function is unknown. Based on the developed model, a reinforcement learning algorithm is applied to solve the DED problem under the wind uncertainty. Simulation results illustrate the effectiveness of the algorithm.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"12 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":"115290401","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
Path Planning of Mission-driven USVs Based on Stochastic Schemata Exploiter 基于随机模式开发器的任务驱动无人潜航器路径规划
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967704
Liwei Zhi, Y. Zuo, Tieshan Li
{"title":"Path Planning of Mission-driven USVs Based on Stochastic Schemata Exploiter","authors":"Liwei Zhi, Y. Zuo, Tieshan Li","doi":"10.1109/DOCS55193.2022.9967704","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967704","url":null,"abstract":"In recent years, the research on unmanned surface vessels (USVs) has become a new hot spot in the development of intelligent applications in the shipping industry of various countries. With the gradual maturity and popularization of modern information technologies such as computer technology and artificial intelligence, the research on USVs has scientific and technological support, and is developing from theoretical research to application practice. Among them, the autonomous assignment and decision-making coordination of multi-target tasks is one of the important research topics for autonomous navigation of USVs. At the same time, the path planning of UAVs also plays a crucial role in autonomous assignment and navigation. In view of the above points, this paper proposes a heuristic optimization algorithm based on stochastic schemata exploiter (SSE). It is used to solve the path optimization problem of USVs for mission requirements. In the experiment, two combinations of two USVs are considered, and the paths are optimized in the two cases of jointly completing the task and cooperatively completing the task. The algorithm combines the heuristic information of the distribution structure of static obstacles in the environment, expands the obstacles and optimizes the node selection of the USV, so that the USV can avoid the obstacles with a higher probability and find an excellent feasible path, and improve the global search ability. Compared with the genetic algorithm (GA) through simulation experiments, the proposed algorithm presents a significant improvement in timeliness and path optimization.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"262 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":"115734172","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
Urban Cold Chain Logistics Vehicle Path Optimization Based on IOT Real-Time Traffic 基于物联网实时交通的城市冷链物流车辆路径优化
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967775
Yanan Huang, Lin Pan
{"title":"Urban Cold Chain Logistics Vehicle Path Optimization Based on IOT Real-Time Traffic","authors":"Yanan Huang, Lin Pan","doi":"10.1109/DOCS55193.2022.9967775","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967775","url":null,"abstract":"As the standard of living continues to improve,people’ s daily requirement for fresh products is also growing. This study considers the real-time traffic congestion, divides the road sections, and calculates the actual travel time of each sub-section, analyzes the transportation cost, establishs a mathematical model with the goal of minimizing the cost and solved by improved genetic algorithm. In addition, this study explores effects of discriminate traffic congestion levels on vehicle paths and costs.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"62 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":"126198407","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
Data-Driven Optimal Control for Multi-Player Non-Zero-Sum Games with Unknown Dynamics 动态未知的多人非零和博弈的数据驱动最优控制
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967753
Liao Zhu, Hongbing Xia, Jiaxu Hou, Ping Guo
{"title":"Data-Driven Optimal Control for Multi-Player Non-Zero-Sum Games with Unknown Dynamics","authors":"Liao Zhu, Hongbing Xia, Jiaxu Hou, Ping Guo","doi":"10.1109/DOCS55193.2022.9967753","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967753","url":null,"abstract":"This paper focuses on optimal control problems of discrete-time nonlinear multi-player non-zero-sum games with unknown dynamics. Based on adaptive dynamic programming, a data-driven adaptive critic control method is developed to obtain the optimal strategies. In order to solve multi-player non-zero-sum games, a new globalized dual heuristic dynamic programming design is proposed without a model network. The coupled Hamilton-Jacobi equations are solved by previous and current value functions for the temporal difference errors. Neural networks are used to approximate value functions and optimal strategies, respectively. The weight updating rules for critic networks and action networks are tuned based on the observing data accrued along system trajectories. The stability analysis of all neural network weights is given by the Lyapunov approach. Simulation results are included to verify the performance of the proposed optimal control scheme.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"91 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":"124426728","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
DOCS 2022 Cover Page DOCS 2022封面
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/docs55193.2022.9967698
{"title":"DOCS 2022 Cover Page","authors":"","doi":"10.1109/docs55193.2022.9967698","DOIUrl":"https://doi.org/10.1109/docs55193.2022.9967698","url":null,"abstract":"","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"29 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":"124753644","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
Topology Design for Multiple Unmanned Surface Vessels Cooperative Control in Polymorphic Networks 多态网络中多艘无人水面舰艇协同控制拓扑设计
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967745
Yuzhou Lu, Qihe Shan, Pu Zhang, Tie-shan Li
{"title":"Topology Design for Multiple Unmanned Surface Vessels Cooperative Control in Polymorphic Networks","authors":"Yuzhou Lu, Qihe Shan, Pu Zhang, Tie-shan Li","doi":"10.1109/DOCS55193.2022.9967745","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967745","url":null,"abstract":"With the development of the Marine power and the increasingly complex tasks and working environments of offshore operations, In view of the limitations of the cooperative control of a single multi-unmanned surface vessels system in a unilateral communication network, In this paper, a communication topology reconstruction method for the cooperative control of multiple multi-unmanned surface vessels systems in polymorphic network is studied. Firstly, a multi-lateral distributed cooperative control system framework for multiple multi-unmanned surface vessels is constructed based on a multi-agent system in polymorphic network. Secondly, for the formation of multiple multi-unmanned surface vessels that perform different tasks after networking, a communication topology reconstruction method is proposed, and a distributed control protocol is designed based on the external equitable partition to achieve multi-consensus. Finally, a simulation example is given to verify the effectiveness of the proposed method.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"18 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":"122124657","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
Quality prediction of industrial polyethylene process with robust long short term memory model 基于稳健长短期记忆模型的工业聚乙烯工艺质量预测
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/docs55193.2022.9967703
Qiao Liu, Weiwei Guo, Liangfeng Xu, Zengliang Gao, Yi Liu
{"title":"Quality prediction of industrial polyethylene process with robust long short term memory model","authors":"Qiao Liu, Weiwei Guo, Liangfeng Xu, Zengliang Gao, Yi Liu","doi":"10.1109/docs55193.2022.9967703","DOIUrl":"https://doi.org/10.1109/docs55193.2022.9967703","url":null,"abstract":"A challenge for construction of accurate soft sensors in the process industries is that industrial process data often contains various noise and outliers. A robust long short term memory (LSTM) neural network with the maximum correntropy criterion (MCC) is proposed to build a reliable soft sensor model. The proposed model employs an MCC-based objective function centred on a Gaussian kernel. Without tedious preprocessing approaches for process data, the proposed model can assign smaller weights to outliers to reduce their negative effects on prediction. Consequently, it can achieve better prediction performance compared with the traditional LSTM soft sensor without robust strategy. The quality prediction results on an industrial polyethylene process demonstrate its effectiveness and advantages.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"29 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":"123259170","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
Doppler location algorithm and performance analysis of low orbit constellation 低轨道星座多普勒定位算法及性能分析
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967747
Huaijian Li, Chao Yin, Xiaojing Du, Yanbo Wei
{"title":"Doppler location algorithm and performance analysis of low orbit constellation","authors":"Huaijian Li, Chao Yin, Xiaojing Du, Yanbo Wei","doi":"10.1109/DOCS55193.2022.9967747","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967747","url":null,"abstract":"Because of the need of radio backup navigation, Doppler localization algorithm based on low-orbit constellation is analyzed and simulated. Compared with low-orbit single-star Doppler location, low-orbit multi-star Doppler location is less affected by the initial iteration point, and low-orbit multi-star Doppler location needs to converge in short time. Through the comparative analysis and simulation of multi-star Doppler location of low-orbit constellation and medium-orbit constellation, it is concluded that the multi-star Doppler location is more accurate under low-orbit constellation. At the same time, the more stars can be seen in the process of multi-star Doppler localization, the higher the positioning accuracy is.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"45 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":"131460440","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
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