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2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)最新文献

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Battery Degradation Prediction Using Incremental Capacity Analysis Based on Real-world Data 基于实际数据增量容量分析的电池退化预测
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00065
Shiyu Liu, Yifan Wang, Hefu Sun, Qixian Mei
{"title":"Battery Degradation Prediction Using Incremental Capacity Analysis Based on Real-world Data","authors":"Shiyu Liu, Yifan Wang, Hefu Sun, Qixian Mei","doi":"10.1109/MLISE54096.2021.00065","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00065","url":null,"abstract":"Power battery degradation is inevitable during usage and it greatly affects the overall performance of the electric vehicle (EV). Therefore, reasonable state of health evaluation of power battery plays a vital role in ensuring safe and reliable operation of EVs. In this paper, a robust battery degradation prediction model is established based on real-world operational data of one specific EV. The method overcomes the difficulty lying in data pre-processing and feature extraction by systematically incorporating incremental capacity analysis, Gaussian smoothing and decision tree regression. Results show that the proposed estimation model can accurately predict the driving mileage with the maximum relative absolute error is beneath X%. Considering the low computational requirement of the proposed method, it has great potential to be applied and implemented in real-world battery management system on EV s.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"263-264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114150326","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
Adaptive Asynchronous Federated Learning for Edge Intelligence 面向边缘智能的自适应异步联邦学习
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00059
Wang Zhaohang, Xia Geming, Chen Jian, Yu Chaodong
{"title":"Adaptive Asynchronous Federated Learning for Edge Intelligence","authors":"Wang Zhaohang, Xia Geming, Chen Jian, Yu Chaodong","doi":"10.1109/MLISE54096.2021.00059","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00059","url":null,"abstract":"Edge intelligence has received great attention for the rapid development and wild application of edge computing and artificial intelligence. As a key technology in edge intelligence for its ability of privacy protection, federated learning faces many problems when deployed in an edge environment. The staleness effect causes by device heterogeneity make the performance of synchronous federated learning limited by these slower devices. And algorithm may also obtain a worse model for statistical heterogeneity. In this paper, we develop an adaptive asynchronous federated learning for edge intelligence to solve the above problems. To improve accuracy and stability of the algorithm, we realize a balance between synchronous and asynchronous settings and implement an adaptive optimization method. At last, we verify the performance in an experiment with heterogeneous settings.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115021403","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: 3
Critical Node Identification based on Attention Flow Networks 基于注意流网络的关键节点识别
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00025
Manfu Ma, Xiangping Wang, Yong Li, Qiang Zhang, Changqing Wang
{"title":"Critical Node Identification based on Attention Flow Networks","authors":"Manfu Ma, Xiangping Wang, Yong Li, Qiang Zhang, Changqing Wang","doi":"10.1109/MLISE54096.2021.00025","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00025","url":null,"abstract":"The identification of critical nodes in complex networks has been extensively studied, but little research has been done on the identification of critical nodes in attentional flow networks. Based on the massive online user behavior data provided by CNNIC, this paper proposed a key node identification model GAT-RL (Graph Attention Networks and Reinforcement Learning) by effectively using the node characteristics and the impact on the network after node removal. Firstly, a directed weighted attentional flow network was constructed based on online user behavior data. Then Graph Attention Networks (GATs) were used to aggregate the neighborhood features of each node in the network to obtain a vector representation of each node. Finally, the vector representation of each node is mapped to the corresponding quality score in combination with reinforcement learning. The critical node ranking is obtained based on the scores. Experiments show that when using the four methods of the GAT-RL model, H-index, degree centrality (Degree) and graph convolutional neural network (RCNN) to identify key nodes in the attention flow network, the GAT-RL model has the most rapid decrease in network connectivity during the identification process. When the node removal ratio is 4%, the connectivity of the remaining graph is about 0.367. When the node removal ratio reaches 13%, the connectivity of the remaining graph is close to 0. Therefore, the GAT-RL model can quickly and accurately identify the critical nodes in the attention flow network.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133783625","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
Network Security Intelligence Information Extraction 网络安全智能信息提取
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00043
Hang Yang, Haosen Wang, Huang Peng, Deqi Cao, Yuntao Zhang, Yajie Dou
{"title":"Network Security Intelligence Information Extraction","authors":"Hang Yang, Haosen Wang, Huang Peng, Deqi Cao, Yuntao Zhang, Yajie Dou","doi":"10.1109/MLISE54096.2021.00043","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00043","url":null,"abstract":"With the continuous development of digitization, there are many invisible threats behind the increasingly developed and complex network. Network security texts are mainly published in the form of Network Threat Intelligence on major network community platforms. In this paper, information extraction technology is used to automatically identify security related entities, relationships, attributes and other information from the network security text. Unstructured text data is transformed into structured expression which is convenient for storage and analysis, and presented in the form of graph data. It provides guidance for technicians to save time, and provides network security decision support for high-level.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132743310","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
Epileptic Seizure Detection Based on Multidimensional Feature Extraction 基于多维特征提取的癫痫发作检测
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00035
Sha-Sha Xu, Y. Piao, Enjia Li, Yue Wang
{"title":"Epileptic Seizure Detection Based on Multidimensional Feature Extraction","authors":"Sha-Sha Xu, Y. Piao, Enjia Li, Yue Wang","doi":"10.1109/MLISE54096.2021.00035","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00035","url":null,"abstract":"Epilepsy is an acute and recurrent neurological disease. Its main clinical symptoms are paroxysmal convulsions, sensory disorders, consciousness and mental disorders, which seriously affect the daily life and work of patients. Seizure detection has always been a challenging work. With the increase of the incidence of epilepsy, high-performance epilepsy automatic detection algorithm can reduce the workload of medical workers in clinic, and has important significance in clinical medical research. This paper combines the characteristics of frequency domain and time domain with nonlinear analysis characteristics to extract features of EEG signals. Firstly, the average Periodic diagram method is used to calculate the power spectral density features, and then the wavelet transform is used to obtain the time domain analysis features. Next, the permutation entropy of five different rhythms are obtained by permutation entropy and information entropy algorithms. Finally, the three features with different dimensions are input into a linear classifier as a single feature to identify seizure and non-seizure signals. The performance of the proposed detection algorithm is evaluated by experiments on the epileptic EEG data-set of the University of Bonn. Experimental results show that the proposed method has a high classification accuracy, which can reach 95. 8%.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116589254","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
Design of intelligent irrigation and soil loosening system for Agricultural Internet of things 农业物联网智能灌溉松土系统设计
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00068
Zhang Chen, Bu Xiuli, Li Yueyang, Zhao Yanli
{"title":"Design of intelligent irrigation and soil loosening system for Agricultural Internet of things","authors":"Zhang Chen, Bu Xiuli, Li Yueyang, Zhao Yanli","doi":"10.1109/MLISE54096.2021.00068","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00068","url":null,"abstract":"Aiming at the problem of soil hardening, an intelligent irrigation and soil loosening system is designed. This design uses Arduino microcontroller as the controller. The microcontroller analyzes and processes the humidity value detected by the soil humidity sensor, and displays the data on the LCD screen. When the humidity value is lower than the lower limit value, irrigation and soil loosening are carried out, and irrigation and soil loosening are stopped until the humidity value reaches the upper limit value. Through the Bluetooth communication with the mobile phone, users can see the real-time humidity value on the mobile phone, and control the switch of the water pump, the depth automatic adjustment mechanism and the execution of the soil loosening mechanism through the buttons on the mobile phone. The design is intelligent, saves water resources, saves labor, and improves crop yield.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123877237","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
Liebovitch map enabled Sine Cosine algorithm 利博维奇地图启用了正弦余弦算法
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00064
Juan Zhao, Zheng-Ming Gao
{"title":"Liebovitch map enabled Sine Cosine algorithm","authors":"Juan Zhao, Zheng-Ming Gao","doi":"10.1109/MLISE54096.2021.00064","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00064","url":null,"abstract":"Being derived from the nonlinear dynamics system, the chaos was claimed and confirmed to be a better replacement of the pseudo random numbers in swarm-based nature-inspired algorithms. In this paper, we proposed a new kind of improvement for the Sine Cosine (SC) algorithm. Unlike other chaotic improvements, the chaotic map enabled SC algorithm with Liebovitch map would only add additional chaos to the controlled parameter balancing the exploration and exploitation ratio. Simulation experiments verified the better performance of the chaotic enabled SC algorithm than the original version.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"IA-20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126560070","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
Autonomous decision-making method of transportation process for flexible job shop scheduling problem based on reinforcement learning 基于强化学习的柔性作业车间调度问题运输过程自主决策方法
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00049
Jun Yan, Zhifeng Liu, Tao Zhang, Yueze Zhang
{"title":"Autonomous decision-making method of transportation process for flexible job shop scheduling problem based on reinforcement learning","authors":"Jun Yan, Zhifeng Liu, Tao Zhang, Yueze Zhang","doi":"10.1109/MLISE54096.2021.00049","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00049","url":null,"abstract":"With the development of intelligent manufacturing technology, automatic guided vehicle (AGV) has been widely used in workshop logistics transportation. However, the complex and changeable production process requires efficient and dynamic transportation and distribution. In this paper, based on the results of process scheduling, a method of independent decision-making transportation process is studied. A transportation strategy training method with breakpoint continuation and hierarchical feedback is proposed based on deep Q-network (DQN). Transportation scheduling can be quickly decided and adjusted to adapt to dynamic and changeable orders. The method is applied to the FJSP problem, and the data experiments show the effectiveness of the method.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121211165","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: 2
Research on Application of UAV in transmission line engineering construction 无人机在输电线路工程建设中的应用研究
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00088
Z. Yuan
{"title":"Research on Application of UAV in transmission line engineering construction","authors":"Z. Yuan","doi":"10.1109/MLISE54096.2021.00088","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00088","url":null,"abstract":"With the development of science and technology, the role of UAV in the erection of transmission lines has gradually become prominent, and has gradually become an important means of transmission line erection. Small drones not only have the flexibility of ordinary drones, but also have many advantages such as small size, light weight, low safety risk, unmanned operation, and high efficiency. Therefore, small UAVs are used in electrical maintenance. Based on this, this paper studies the application method of UAV in the construction of transmission line project, effectively solves the relationship between river closure, safety, progress and environmental protection in the transmission line project, and can save the construction cost.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122855613","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
Cylinder body into the total side hole special fixture design 缸体进总侧孔专用夹具设计
2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE) Pub Date : 2021-07-01 DOI: 10.1109/MLISE54096.2021.00091
Qin Nan
{"title":"Cylinder body into the total side hole special fixture design","authors":"Qin Nan","doi":"10.1109/MLISE54096.2021.00091","DOIUrl":"https://doi.org/10.1109/MLISE54096.2021.00091","url":null,"abstract":"In order to realize the processing of the φ2-41mm, φ64.5 and φ 16mm counterbore holes on the side of the engine cylinder, a set of special hydraulic clamps has been designed. In considering of the structural properties of the parts of the cylinder's Block of the engine, a key for both sides is arranged for the parts Positioning. On the other hand, a special clamping mechanism is designed in need to meet the requirement for the cutting tool in one pass on the turn of processing in batches. Cutting force and clamping force are calculated in the same time and the type of the hydraulic cylinder has been selected. Practice has proved that this set of fixture mechanism is simple, easy to operate and can effective improving production efficiency.","PeriodicalId":430495,"journal":{"name":"2021 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130972149","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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