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

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Prescribed Performance Adaptive Tracking Control of Nonlinear Mass-Spring-Damper System with Stochastic Disturbance 随机扰动下非线性质量-弹簧-阻尼系统的预定性能自适应跟踪控制
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967782
Yanli Liu, Tao Hong
{"title":"Prescribed Performance Adaptive Tracking Control of Nonlinear Mass-Spring-Damper System with Stochastic Disturbance","authors":"Yanli Liu, Tao Hong","doi":"10.1109/DOCS55193.2022.9967782","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967782","url":null,"abstract":"In this paper, we consider the prescribed performance control problem for a nonlinear mass-spring-damper system with unknown dead-zone output and stochastic disturbance. Firstly, a smooth approximate model is used to solve the problem of nondifferentiable of the output dead-zone at the turning point, and a Nussbaum-type function is used to deal with the impact of the unknown dead-zone during the control design. Besides, the fuzzy logic system is used to approximate the unknown nonlinear function in the system, and the system tracking error is always ensured to be within the preset error boundaries by presetting the performance function. Subsequently, the system is proved to be stable using the Lyapunov function, and it is also shown that all closed-loop signals under this system are bounded in probability. Finally, the effectiveness of the control scheme is verified by simulink simulation.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"19 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":"130278849","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
Substation switching device identification method based on deep learning 基于深度学习的变电站开关设备识别方法
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967743
Liang Wang, Qilong Kou, Qinggai Zeng, Zhonghao Ji, Leiyue Zhou, Shuai Zhou
{"title":"Substation switching device identification method based on deep learning","authors":"Liang Wang, Qilong Kou, Qinggai Zeng, Zhonghao Ji, Leiyue Zhou, Shuai Zhou","doi":"10.1109/DOCS55193.2022.9967743","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967743","url":null,"abstract":"In order to realize the real-time and efficient detection of substation switching device status, and to solve some existing problems of substation inspection system, such as the limited degree of automation and the need for human intervention to solve the problem. This paper proposes a status recognition method of substation switching device based on deep learning. The method obtains image data by the optical camera of an inspection robot, and uses the deep learning technology to analyze and detect the data. In this method, firstly, the image data of substation switching device is selected and marked as the data set of model training, then the Yolov3 target detection network is used to build an automatic status recognition model of substation switch device. Experimental results show that this method can automatically identify the substation switching device status, and the recognition accuracy reached 97%.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"6 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":"124516817","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
Improved YOLOV3 Surveillance Device Object Detection Method Based on Federated Learning 基于联邦学习的改进YOLOV3监控设备目标检测方法
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967481
Huiping Li, Kangning Yin, Xinhui Ji, Yin Liu, Tingting Huang, Guangqiang Yin
{"title":"Improved YOLOV3 Surveillance Device Object Detection Method Based on Federated Learning","authors":"Huiping Li, Kangning Yin, Xinhui Ji, Yin Liu, Tingting Huang, Guangqiang Yin","doi":"10.1109/DOCS55193.2022.9967481","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967481","url":null,"abstract":"In the process of smart city construction, a large number of video monitoring devices are used for urban security. However, these devices produce a large amount of monitoring data, which will make the task of retrieving specific goals difficult to achieve. At the same time, as people attach importance to privacy protection, it is difficult for data interaction between different enterprise devices. In this paper, in order to speed up the operation efficiency and break the data island of the IoT devices, we make the edge device of video surveillance for object detection based on federated learning, and improve YOLOv3. In order to simplify the model, Resnet50 is used to replace Darkent-53. We propose Multi-Dimensional and Multi-Scale (MDMS) feature pyramid to better use features to detect objects at different scales. We design the Improved OutLook Attention (IOA) module to make the network perform better in fine-grained feature. The final experimental results show that our network has greatly improved video surveillance object detection. Our method improves the mapping of the model and reduces the number of model parameters. The model size is compressed from 469.64 MB to 180.39 MB. However, the map is increased from 83.5% to 85.8%, which makes the video monitoring equipment more intelligent and enhances the ability of privacy protection.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"16 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":"116193160","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
Highlight Removal with Orthogonal Decomposition 用正交分解去除高光
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967699
Zhen Zhang, Weihong Ren, Yang Lu, Shijun Zhou, Yandong Tang, Jiandong Tian
{"title":"Highlight Removal with Orthogonal Decomposition","authors":"Zhen Zhang, Weihong Ren, Yang Lu, Shijun Zhou, Yandong Tang, Jiandong Tian","doi":"10.1109/DOCS55193.2022.9967699","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967699","url":null,"abstract":"In this paper, based on orthogonal decomposition, we present a robust and effective method for highlight removal. First, we obtain the reflectance image of an image through orthogonal decomposition. Then, the reflectance image is used to cluster the image. According to the clustering results, illumination chromaticity is estimated. Finally, we separate diffuse and specular reflections per pixel according to the distance from each pixel chromaticity to illumination chromaticity, where the diffuse reflection image is the highlight removal image. According to our extensive experimental results, the proposed method outperforms all the existing state-of-the-art (SOTA) methods according to the Peak-Signal-to-Noise-Ratio (PSNR) and the Structural Similarity (SSIM) Index score.","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":"125464268","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
Finite-time Synchronization of Complex Networks with Intermittent Event-Triggered Control 具有间歇事件触发控制的复杂网络的有限时间同步
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967758
Rongqiang Tang, Xinsong Yang
{"title":"Finite-time Synchronization of Complex Networks with Intermittent Event-Triggered Control","authors":"Rongqiang Tang, Xinsong Yang","doi":"10.1109/DOCS55193.2022.9967758","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967758","url":null,"abstract":"This conference focuses on finite-time synchronization (FtSyn) of complex networks(CNs) by designing an intermittent event-triggered control. First, an improved finite-time stability with intermittent divergence of system’s state is provided, which does not demand all the intervals of convergence and divergence are periodic and proportional to greater than 1. Then, with the aid of multiple Lyapunov functions and convex combination techniques, sufficient conditions ensuring FtSyn of CNs are obtained, which are formulated by a set of linear matrix inequalities. Finally, a numerical application of the suggested theories to Chua’s system is offered to illustrate their usefulness.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"6 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":"133352753","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
Continuous Berth Allocation Considering Carbon Emission and Uncertainty 考虑碳排放和不确定性的连续泊位分配
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967702
Feifei Yu, Fei Teng, Qihe Shan, Tieshan Li, Yang Xiao
{"title":"Continuous Berth Allocation Considering Carbon Emission and Uncertainty","authors":"Feifei Yu, Fei Teng, Qihe Shan, Tieshan Li, Yang Xiao","doi":"10.1109/DOCS55193.2022.9967702","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967702","url":null,"abstract":"For port emission reduction, berth allocation is one of the key decisions. This paper tackles a continuous berth allocation problem under the low-carbon target, taking into account the uncertainty of vessels’ arrival time and handling time. A bi-level bi-objective model is constructed aiming at minimizing the average carbon emission, together with the range of the carbon emission which is introduced for the improvement of robustness. The objective functions in the model contain another optimization problem, so the model is simplified via a hierarchical optimization method. Then a multi-objective genetic algorithm is designed to solve the model and the validity is demonstrated by a data case.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"25 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":"125040505","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
Hybrid Estimation of Distribution Based on Knowledge Transfer for Flexible Job-shop Scheduling Problem 基于知识转移的柔性作业车间调度混合分布估计
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967485
Lulu Cao, Min Jiang, Liang Feng, Qiuzhen Lin, Renhu Pan, Kay Chen Tan
{"title":"Hybrid Estimation of Distribution Based on Knowledge Transfer for Flexible Job-shop Scheduling Problem","authors":"Lulu Cao, Min Jiang, Liang Feng, Qiuzhen Lin, Renhu Pan, Kay Chen Tan","doi":"10.1109/DOCS55193.2022.9967485","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967485","url":null,"abstract":"In this work, we introduce a new method called G-EDA for solving flexible job-shop scheduling problems (FJSP). Based on the investigation of current works, it can be found that the solution of FJSP mainly focuses on the intelligent optimization algorithm, such as the genetic algorithm, which obtains new population through crossover and mutation. When searching individuals, this algorithm does not fully use the knowledge hidden in the excellent individuals in the previous generation population, and its performance is poor when facing high-dimensional problems. This paper hopes to find a method to find the distribution law of high-quality individuals in the previous generation population and transfer the knowledge contained in the previous generation population to the next generation to improve the performance of the algorithm. In this paper, we propose a hybrid estimation of distribution algorithm using population grouping mechanism(G-EDA). We conduct numerical simulations based on two sets of international standard examples. And we compare G-EDA with some existing advanced algorithms. The results show that G-EDA is effective and practical in solving multi-objective FJSP.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"25 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":"125332210","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 Multi-Objective Direct Heuristic Dynamic Programming Based Tracking Control for Wastewater Treatment Process 基于多目标直接启发式动态规划的污水处理过程跟踪控制
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967740
Weiwei Cao, Qinmin Yang, Wenchao Meng
{"title":"A Multi-Objective Direct Heuristic Dynamic Programming Based Tracking Control for Wastewater Treatment Process","authors":"Weiwei Cao, Qinmin Yang, Wenchao Meng","doi":"10.1109/DOCS55193.2022.9967740","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967740","url":null,"abstract":"WASTEWATER treatment process (WWTP) plays an important role in human production and life. It reduces wastewater by biochemical treatment to protect the environment. Meanwhile the highly nonlinear WWTP is difficult to model mathematically with unknown disturbances and strong coupling. In the past decades, many great efforts have been made to improve the control performance, such as on-off control [1] , PID control, feed-forward control [2] , fuzzy-based control [3] , neural network (NN)-based method [4] , and model predictive control (MPC) [5] , [6] , etc. While traditional control strategies are tuned by experience offline, fuzzy-based method is difficult to implement when the expert experience is hard to obtain, and MPC relies on a precise prediction model in advance.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"1 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":"129150923","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
Ship trajectory prediction based on transformer model 基于变压器模型的船舶轨迹预测
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967723
Kaihang Kang, Chuang Zhang, Chen Guo
{"title":"Ship trajectory prediction based on transformer model","authors":"Kaihang Kang, Chuang Zhang, Chen Guo","doi":"10.1109/DOCS55193.2022.9967723","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967723","url":null,"abstract":"In view of the increasingly complex maritime traffic situation, in order to meet the demand of ship trajectory prediction accuracy, based on the large amount of ship trajectory data contained in the AIS(Automatic Identification System) and the encoder decoder construction mechanism of the transformer model, a transformer model is proposed to decode with the full connection layer instead of the decoder. According to the existing ship trajectory data, the model is trained to predict the future ship trajectory. The experimental results show that the error between the predicted trajectory information and the real trajectory information is small, which proves the effectiveness of the model.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"15 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":"129601048","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
Efficient Named Entity Recognition Based on Broad Learning System and BERT 基于广义学习系统和BERT的高效命名实体识别
2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967729
Yudi Wang, Y. Zuo, Tieshan Li, C. L. P. Chen
{"title":"Efficient Named Entity Recognition Based on Broad Learning System and BERT","authors":"Yudi Wang, Y. Zuo, Tieshan Li, C. L. P. Chen","doi":"10.1109/DOCS55193.2022.9967729","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967729","url":null,"abstract":"In this paper, we propose an efficient approach for named entity recognition (NER). This paper applies the broad learning system (BLS) to NER task, which includes the feature learning and incremental learning processes. In the feature learning of BLS, the calculation of each new feature node involves only matrix multiplication, and can effectively reduce the amount of calculation to improve efficiency in obtaining rich features. In the incremental learning of BLS, the feature nodes are calculated by active function and ridge regression in order to obtain incremental nodes. In this paper, we combine the BLS with bidirectional encoder representations from transformers (BERT) and conditional random fields (CRF) algorithms to conduct NER of English corpus. Firstly, we extract features through BERT. Secondly, we use BLS to calculate the extracted features. Finally, we apply CRF to decoding features. In numerical experiments, NER of English corpus based on BIO schema is used as benchmark, And the proposed method shows higher accuracy and faster training than other baseline methods.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"7 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":"125492762","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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