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

Robot Manipulator Anti-Disturbance Control based on PSO Multi-task Optimization 基于粒子群多任务优化的机器人机械手抗干扰控制

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967483

Yifan Chen, Miaomiao Qu, Xuhua Shi

引用次数: 0

A bi-criterion differential evolution for multimodal multi-objective optimization 多模态多目标优化的双准则微分演化

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967697

Li Yan, He Tian, Yiran Li, X. Chai, Chao Huang, B. Qu

{"title":"A bi-criterion differential evolution for multimodal multi-objective optimization","authors":"Li Yan, He Tian, Yiran Li, X. Chai, Chao Huang, B. Qu","doi":"10.1109/DOCS55193.2022.9967697","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967697","url":null,"abstract":"In this paper, a bi-criterion differential evolution algorithm for multimodal multi-objective optimization is proposed, termed BCDE-MM. A bi-criterion framework based on indicator-based criterion and Pareto criterion is designed. The two criteria are used respectively in the individual and environmental selection to balance the diversity and convergence of the algorithm in objective space. Specifically, a clustering-based indicator fitness assignment scheme is proposed, in which the K-nearest neighbor (KNN) clustering is employed to ensure diversity in the decision space. The indicator-based fitness is assigned in each cluster obtained by KNN based on their distribution in objective space. Consequently, the information of both the decision space and the objective space are considered simultaneously in each subpopulation, which can balance the computing resource assigned to both spaces. In addition, an adaptive mutation method selection strategy is proposed to improve search efficiency. Experimental results verify the effectiveness and superiority of BCDE-MM in solving MMOPs.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"21 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":"133357868","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

Multi-population Cooperative Particle Swarm Optimization with Covariance Guidance 协方差指导下的多种群协同粒子群优化

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967774

Peng Liang, Wei Li, Y. Huang

{"title":"Multi-population Cooperative Particle Swarm Optimization with Covariance Guidance","authors":"Peng Liang, Wei Li, Y. Huang","doi":"10.1109/DOCS55193.2022.9967774","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967774","url":null,"abstract":"The particle swarm optimization algorithm has been widely utilized to address a wide range of different engineering optimization problems due to its few parameters and simple structure. The conventional particle swarm optimization algorithm takes in information from two sources: Global optimal particle and individual optimal particle. However, learning from these two sources alone is inefficient to solve complex high-dimensional problems. Therefore, this paper proposes a multi-population cooperative particle swarm optimization (COVPSO) algorithm with covariance guidance strategy, through the use of a covariance guidance strategy to guide population evolution direction. In COVPSO, the population is divided based on the Euclidean distance from the particle to the global optimal particle, and the population is divided into the elite group, exploratory group, and inferior group. As a result of grouping the population and adopting different strategies, the elite group has good exploitation ability, while the exploration group has good exploration ability, and the inferior groups by introducing a differential mutation operator to improve global exploration ability. Therefore, the population has a good balance between exploration and exploitation. This study utilizes ten benchmark functions and five PSO variants broadly used in the literature to verify the merits of COVPSO to demonstrate its efficiency. The findings of the experiments show that COVPSO has a faster convergence rate and a more precise solution.","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":"114317517","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

Image-Based Trajectory Tracking Control for Wheeled Mobile Robots with ADP 基于图像的ADP轮式移动机器人轨迹跟踪控制

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967720

Zhihua Ouyang, Biao Luo, Xinning Yi

{"title":"Image-Based Trajectory Tracking Control for Wheeled Mobile Robots with ADP","authors":"Zhihua Ouyang, Biao Luo, Xinning Yi","doi":"10.1109/DOCS55193.2022.9967720","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967720","url":null,"abstract":"In this paper, a visual servoing approach based on approximate dynamic programming (ADP) is developed for the trajectory tracking control of mobile robots. First, according to the current image, the desired image and reference image sequence of coplanar feature points are captured by the onboard camera, and the current pose information and desired pose information of the mobile robot can be reconstructed by homography technology. Then, the open-loop system errors are defined by translation and rotation. In order to design the optimal controller for this system, the appropriate control input transformation is adopted. Therefore, a visual servoing approach based on ADP is proposed to achieve the trajectory tracking task for the mobile robot. A critic neural network (NN) structure is used to learn the time-varying solution, namely the optimal value function, of the Hamilton–Jacobi–Bellman (HJB) equation. Since the existence of time-varying terms, which is different from many existing works, the HJB equation is time-varying. Therefore, a NN with time-varying weight structure is designed to approximate the time-dependent value function of the HJB equation. Finally, it is proved that the approach proposed in this paper guarantees that the closed-loop system is uniformly ultimately bounded.","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":"133555963","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

One-class Anomaly Detection with Redundancy Reduction and Momentum Mechanism 基于冗余约简和动量机制的一类异常检测

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967719

Xingbao Zhang, W. Li, Yue Zhao

{"title":"One-class Anomaly Detection with Redundancy Reduction and Momentum Mechanism","authors":"Xingbao Zhang, W. Li, Yue Zhao","doi":"10.1109/DOCS55193.2022.9967719","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967719","url":null,"abstract":"The objective of anomaly detection is to identify the sample which differs in some known data. In practice, anomaly class is usually hard to obtain and consumptive to label, while unsupervised learning and one-class classification are most widely used to solve this problem. Only a set of data from the specific class are given in the training phase, and the remaining categories will be considered as abnormal. In this paper, inspired by the success of deep learning and Support Vector Data Description (SVDD) of decision boundary-based, a novel idea that combining SVDD with redundant information reduction and momentum update mechanism named RRM-SVDD is proposed to address the anomaly detection problem. With the existence of trivial solutions for SVDD, an objective function is designed to avoid such situation by computing the dimension correlation matrix of the output vector from the feature extraction network, while optimizing it as the identity matrix to make any two dimensions as linearly independent as possible in the pretraining phase, that causes the effective for SVDD to describe the distribution of normal data in the feature space and reduce the probability of model collapse. Meanwhile, the momentum update mechanism is applied to learn the global hyperparameter center C by considering the previous epoch information in the next training period. To evaluate the performance of RRM-SVDD, related experiments on MNIST and CIFAR-10 image benchmark dataset have been conducted, achieved state-of-the-art anomaly detection accuracy and robustness in most categories than comparison methods.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"74 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":"124781094","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

Classification of Pathological Images of Skin Diseases Based on Deep Learning 基于深度学习的皮肤病病理图像分类

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967728

Ke Liu, Tao Huang, Zhaoxia Guo

{"title":"Classification of Pathological Images of Skin Diseases Based on Deep Learning","authors":"Ke Liu, Tao Huang, Zhaoxia Guo","doi":"10.1109/DOCS55193.2022.9967728","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967728","url":null,"abstract":"Skin cancer is one of the highest incidences of cancer, the incidence of the population covers all ages. However, the diagnosis process of skin diseases is complex, which requires doctors to observe and locate the injured sites first, then slice the living tissue under the microscope, which challenges doctors' timely diagnosis and medical treatment plan. Therefore, a more accurate classification algorithm of skin diseases has essential significance and clinical application value for timely skin cancer diagnosis. In recent years, most studies on dermatology algorithms have focused on the binary classification of benign and malignant dermatoses. However, there are many kinds of dermatoses, and each kind of dermatoses has different pathogenesis and treatment methods. Based on this, this paper applies convolutional neural network to eight classification of dermatosis. Furthermore, the size and shape of skin lesions are not the same, and the presence of artifacts such as hair and veins around the injured sites also make an accurate diagnosis more difficult. Therefore, this paper introduces the attention mechanism on the basis of the original Inception-Resnet-v2 network, and at the same time, enhances the original data. Finally, we uses the method of transfer learning to conduct experiments on the training dataset of ISIC 2019 challenge. The results show that the average classification accuracy of the method used in this paper is more than 85%, and the AUC score of each category is above 0.95, which shows that the classifier has good performance.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"47 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":"121260575","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

Knowledge transfer for Object Detection with Evolution architecture search 基于进化体系结构搜索的目标检测知识转移

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967711

Jiaquan Li, Haokai Hong, Minghui Shi, Qiuzhen Lin, Fenfen Zhou, Kay Chen Tan, Min Jiang

{"title":"Knowledge transfer for Object Detection with Evolution architecture search","authors":"Jiaquan Li, Haokai Hong, Minghui Shi, Qiuzhen Lin, Fenfen Zhou, Kay Chen Tan, Min Jiang","doi":"10.1109/DOCS55193.2022.9967711","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967711","url":null,"abstract":"Deep learning has been proved to achieve excellent results in various fields, and appropriate network architecture and sufficient data play an important role. Due to the high cost of annotation for the task of object detection, domain adaptation methods have been introduced in this field. But these methods are based on the rigid network architecture and bound to the input dimension of the adaptive module, which is not only difficult to better balance accuracy and speed of detection model, but also can not use the multi-scale training method, resulting in the reduction of the application scenario of the model. Inspired by this problem, we propose a new object detection method based on multi-scale adversarial domain adaptation and network architecture search. An evolutionary algorithm is adopted to help search the network architecture to balance accuracy and speed. The ability of domain adaptation can also be effectively improved by the searched architecture. The experimental results have demonstrated the significant improvement that benefited from the framework in terms of its performance and computational efficiency in solving unlabeled object detection.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"109 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120866951","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 Time Series Forecast Method for Vessel Trajectory Prediction 船舶航迹预测的时间序列预测方法

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967725

Shaobin Li, Zehan Tan, Yanyu Chen, Weidong Yang, Siyuan Lei, Jiale Zhang

{"title":"A Time Series Forecast Method for Vessel Trajectory Prediction","authors":"Shaobin Li, Zehan Tan, Yanyu Chen, Weidong Yang, Siyuan Lei, Jiale Zhang","doi":"10.1109/DOCS55193.2022.9967725","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967725","url":null,"abstract":"In recent years, alongside the progress of marine vessel information technology, the scale of vessel-related data has grown exponentially. At the same time, maritime monitoring based on vessel data has achieved unprecedented development, so how to effectively manage and supervise the marine operations of vessels is now a widely concerned issue. By predicting the future trajectories of vessels, vessel behavior can be assessed to avoid potential hazards. This paper establishes a pre-processing model of vessel data based on the time series data of vessels. According to the characteristics of vessel data, cleaning, noise reduction, and trajectory extraction are conducted to the data followed by interpolation. Trajectory similarity evaluation is conducted with a time series similarity measurement method, and a trajectory clustering model based on DBSCAN is constructed from the trajectory similarity information. Later, this paper proposes a time series prediction model based on Attention and LSTM. The prediction model adopts an Encoder-Decoder structure. The model takes the time series characteristics of a vessel trajectory as the input to predict the future trajectory of a vessel.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"193 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":"115499653","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 Hybrid State of Health Estimation Method for Lithium Ion Battery 锂离子电池混合健康状态估计方法

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967726

Xinyue Wang, Rui Guo, Jianyong Guo

{"title":"A Hybrid State of Health Estimation Method for Lithium Ion Battery","authors":"Xinyue Wang, Rui Guo, Jianyong Guo","doi":"10.1109/DOCS55193.2022.9967726","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967726","url":null,"abstract":"In order to improve the accuracy and practicability of state of health estimation for lithium-ion batteries, the Improved Arithmetic Particle Swarm Optimization Algorithm (IAPSOA) is proposed in this work. Combined with Deterministically Constructed Cycle Reservoirs with Regular Jumps(CRJ), IAPSOA-CRJ estimation method is proposed. The constant current charging time of the battery is extracted as a health indicator to predict the real capacity series. Then, by improving the Arithmetic Optimization Algorithm(AOA),the search ability and stability of AOA algorithm are improved. This paper also studied the influence of different training set length on the model. Finally, the generalization performance is tested with the trained model on another set of battery data of the same type. IAPSOA algorithm is used to optimize the input matrix parameter, reservoir parameters and regularization coefficient of CRJ network, and compared with Radial Basis Function Neural Network, Elman Neural Network and Optimized Kernel Extreme Learning Machine. The results show that the proposed IAPSOA-CRJ estimation model performs best in all aspects, and has strong robustness and generalization ability.","PeriodicalId":348545,"journal":{"name":"2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS)","volume":"342 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":"124227495","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

Evolution of Online Public Opinions and Situational Control During the COVID-19 Pandemic: A case study from Chengdu, China 新冠肺炎疫情期间网络舆情演变与态势控制——以成都市为例

2022 4th International Conference on Data-driven Optimization of Complex Systems (DOCS) Pub Date : 2022-10-28 DOI: 10.1109/DOCS55193.2022.9967739

Ziqi Pan, Songling Li, Yuyan Luo, Xiaolei Xu, Y. Mou, Xu Liu

{"title":"Evolution of Online Public Opinions and Situational Control During the COVID-19 Pandemic: A case study from Chengdu, China","authors":"Ziqi Pan, Songling Li, Yuyan Luo, Xiaolei Xu, Y. Mou, Xu Liu","doi":"10.1109/DOCS55193.2022.9967739","DOIUrl":"https://doi.org/10.1109/DOCS55193.2022.9967739","url":null,"abstract":"In the age of big data, online public opinions breed and erupt when health emergencies occur. Tourism destinations have attracted much attention because of their unique high traffic and frequent population movements. It is crucial to take reasonable measures to cope with the outbreak of negative public opinion during the COVID-19 Pandemic. This paper uses Python to crawl the sentiment perceptions of tourists towards Tourism destinations during public health emergencies and classifies the sentiment as the dataset. Then, using Netlogo software to build an online opinion model, we simulate four scenarios for what a tourist destination should do to reduce the outbreak of negative public opinion: the release of information by opinion leaders, the change in the number of people contacted by negative public opinion, the change in the speed of dissemination of negative public opinion, and the release of relevant policies. In the four scenarios, it was found that the scenario in which relevant departments issued regulations have the greatest impact on negative public opinions. Changing the speed of public opinion dissemination is the least significant scenario.","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":"115164930","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