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2021 11th International Conference on Information Science and Technology (ICIST)最新文献

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Decentralized Tracking Control for Modular Reconfigurable Robots Using Data-Based Concurrent Learning 基于数据并发学习的模块化可重构机器人分散跟踪控制
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440625
Qiuye Wu, Qiliang Luo, Weichen Luo, Derong Liu, Bo Zhao
{"title":"Decentralized Tracking Control for Modular Reconfigurable Robots Using Data-Based Concurrent Learning","authors":"Qiuye Wu, Qiliang Luo, Weichen Luo, Derong Liu, Bo Zhao","doi":"10.1109/ICIST52614.2021.9440625","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440625","url":null,"abstract":"This paper proposes a decentralized tracking control (DTC) through data-based concurrent learning for modular reconfigurable robots (MRRs) with unknown dynamics. By using the local input-output data and reference trajectories of interconnected subsystems, a neural network (NN)-based local observer is established to acquire the MRR dynamics online. Based on the adaptive dynamic programming algorithm, the local Hamilton- Jacobi-Bellman equation is solved by a local critic NN, whose weight vector is tuned by a concurrent learning-based updating law. Then, the DTC policies are obtained, and the persistence of excitation condition is removed. The tracking error of the entire closed-loop MRR system is guaranteed to be uniformly ultimately bounded by the Lyapunov’s direct method. The simulation on a 2- DOF MRR system demonstrates that the proposed DTC scheme is effective.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116046283","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
Cooperative Output Tracking of Heterogeneous Uncertain Nonlinear Multi-Agent Systems via Distributed Event-Triggered Adaptive Fuzzy Control 基于分布式事件触发自适应模糊控制的异构不确定非线性多智能体系统协同输出跟踪
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440628
Anqing Wang, Lu Liu, Jianbin Qiu
{"title":"Cooperative Output Tracking of Heterogeneous Uncertain Nonlinear Multi-Agent Systems via Distributed Event-Triggered Adaptive Fuzzy Control","authors":"Anqing Wang, Lu Liu, Jianbin Qiu","doi":"10.1109/ICIST52614.2021.9440628","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440628","url":null,"abstract":"In this study, the cooperative output tracking problem is addressed for strict-feedback uncertain nonlinear multiagent systems. A novel distributed adaptive fuzzy control strategy is developed based on the event-triggered transmission scheme. With the proposed approach, only sampled output information needs to be exchanged among the communication network, which not only reduces the communication burden, but also makes the controller implementation more flexible. In addition, Zeno behavior is avoided and the cooperative output tracking error converges to an adjustable set around the origin by choosing different design parameters. The effectiveness of the main result is verified by a simulation example.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116623141","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
Distributed Constrained Online Optimization with Noisy Communication 带噪声通信的分布式约束在线优化
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/icist52614.2021.9440593
Yupei Yang, Yifan Song, Shaofu Yang
{"title":"Distributed Constrained Online Optimization with Noisy Communication","authors":"Yupei Yang, Yifan Song, Shaofu Yang","doi":"10.1109/icist52614.2021.9440593","DOIUrl":"https://doi.org/10.1109/icist52614.2021.9440593","url":null,"abstract":"This paper addresses distributed online optimization problems with time-varying coupled constraints via a group of cooperative agents. The communication among agents suffers from disturbance of noise. By employing primal-dual mirror descent method, we propose a distributed online algorithm with noisy communication for solving such problems. By using the bound of noise, we obtain estimations on both dynamic regret and constraint violation, which depict the effect of communication noise. Then, by choosing certain diminishing step sizes, we theoretically prove that the dynamic regret and constraint violation grow sublinearly, provided that the optimal decision sequence varies slowly and the noise is attenuated. Finally, theoretical results is substantiated by a numerical example.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115047829","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
Segmented CRC-Aided Order Statistical Decoding with Multiple Biases for Short Polar Codes 短极码的多偏差分段crc辅助序统计译码
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440582
Hao Tang, Ming Zhan, Liangxi Liu, Mingjuan Qiu, Fu-Gang Wang, Qian Zhang, Yunkai Feng
{"title":"Segmented CRC-Aided Order Statistical Decoding with Multiple Biases for Short Polar Codes","authors":"Hao Tang, Ming Zhan, Liangxi Liu, Mingjuan Qiu, Fu-Gang Wang, Qian Zhang, Yunkai Feng","doi":"10.1109/ICIST52614.2021.9440582","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440582","url":null,"abstract":"With the advent of 5th generation (5G) mobile communication era, higher requirements are put forward for ultra-reliable and low-latency transmission compared with 4G, especially in the field of short packet communication. In this paper, we propose a segmented cyclic redundancy check aided order statistical decoding algorithm with multiple biases (BIAS- SCRC-OSD) for short polar codes. This algorithm constructs multiple information sets by repeatedly adding bias value, and selects more effective information sets to improve the decoding performance. For further improving the decoding performance, we change the original cyclic redundancy check (CRC) into segment check. The simulation results show that a suitable bias value can significantly improve the decoding performance with a small increase in computational complexity. Compared with the original CRC-aided order statistical decoding (OSD) algorithm, the proposed algorithm has a gain of about 0.8 dB at target bit error rate (BER) 10–4 with code rate R = 0.5 and code length N = 64.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123403118","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
Bearing-only Formation Control of First-Order Discrete-Time Multi-Agent Systems 一阶离散多智能体系统的纯方位编队控制
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440605
Jing Tian, Wenfeng Hu
{"title":"Bearing-only Formation Control of First-Order Discrete-Time Multi-Agent Systems","authors":"Jing Tian, Wenfeng Hu","doi":"10.1109/ICIST52614.2021.9440605","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440605","url":null,"abstract":"In this paper, we address the formation control problem of first-order discrete-time multi-agent systems, where the control law for each agent only depends on the relative bearings to its neighboring agents. Different from the continuous-time multi-agent systems, the sampling time step in the discrete-time counterpart is required to be upper bounded by some properly designed constant, such that the bearing-only formation can be achieved. Finally, the simulations are provided to verify the correctness of theoretical results.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129405931","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
Using Deep Learning Techniques to Predict 10-Year US Treasury Yield 使用深度学习技术预测10年期美国国债收益率
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440560
Lihchyun Shu, Ju-Kun Chou
{"title":"Using Deep Learning Techniques to Predict 10-Year US Treasury Yield","authors":"Lihchyun Shu, Ju-Kun Chou","doi":"10.1109/ICIST52614.2021.9440560","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440560","url":null,"abstract":"The yield to maturity of United States Treasury securities is a decisive indicator of the economic cycle in the United States, and it is also one of the most critical interest rate references for capital markets worldwide. This study investigates the effectiveness of applying deep learning methods in financial prediction. Specifically, a deep learning model is trained by using the yields of various United States Treasury securities of different maturities to predict the 10-year yield.We collect time series data from the daily yields of United States Treasury securities from January 1990 to November 2018, which are subsequently preprocessed for the establishment of a long short-term memory model. By using this model, we predict the 10-year yield with a resulting mean squared error as low as 0.0063 for the test data sets.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125344514","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
Uncertain Service Skyline Queries Based on Cloud Model in Mobile Application* 移动应用中基于云模型的不确定服务Skyline查询*
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440619
Longchang Zhang, Gyan Amos, Jing Bai, Xinyue Zhang
{"title":"Uncertain Service Skyline Queries Based on Cloud Model in Mobile Application*","authors":"Longchang Zhang, Gyan Amos, Jing Bai, Xinyue Zhang","doi":"10.1109/ICIST52614.2021.9440619","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440619","url":null,"abstract":"The QoS based on mobile user ratings shows the fuzziness and randomness, and the number of services with the same function is larger, which makes service selection based on QoS hard. To solve above issue, this paper firstly proposes to use cloud model to describe QoS based on mobile user ratings. Then to reduce the search range for optimal service, this paper puts forward uncertain service Skyline calculation method based on cloud model and designs four kinds of uncertain service Skyline query algorithms (BNL_CM, D&C_CM, NN_CM and BBS_CM). Examples and experiments show that: 1) the cloud model has better performance in the description of QoS than the mean, interval number, fuzzy numbers, and random number; 2) Uncertain service Skyline can effectively reduce the service search range; 3) BBS_CM has better performance compared to BNL_CM, D&C_CM and NN_CM.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128756413","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
Metaheuristics for Index-Tracking with Cardinality Constraints 基数约束下索引跟踪的元启发式算法
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440584
Man-Chung Yuen, Sin-Chun Ng, Man-Fai Leung, Hangjun Che
{"title":"Metaheuristics for Index-Tracking with Cardinality Constraints","authors":"Man-Chung Yuen, Sin-Chun Ng, Man-Fai Leung, Hangjun Che","doi":"10.1109/ICIST52614.2021.9440584","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440584","url":null,"abstract":"As one of the passive investment strategies, index-tracking aims to replicate market indexes to reproduce market performance. It is widely used for long-term investment. Full replication and partial index-tracking are common approaches for index-tracking problems. Although full replication tracks the chosen market index perfectly, the transaction cost is relatively high in practice. Therefore, partial index-tracking is desired that can reduce the transaction cost and avoid illiquid assets. The partial index-tracking approach selects the subset of a benchmark index and applies restrictions for the numbers of stocks with cardinality constraints. The constrained problem is converted into an unconstrained problem by adding the penalty term. This paper is concerned with the sparse index-tracking problem with cardinality constraints by various metaheuristics. Various metaheuristics are used to deal with the sparse index-tracking problem, and their performances are compared. Also, various penalty values are adopted to test the performance of the compared algorithm.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"os-12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127690204","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
EPnet: A general network to predict enhancer-promoter interactions EPnet:预测增强子-启动子相互作用的通用网络
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440647
Zihang Wang, Lin Zhou, Shuai Jiang, Wei Huang
{"title":"EPnet: A general network to predict enhancer-promoter interactions","authors":"Zihang Wang, Lin Zhou, Shuai Jiang, Wei Huang","doi":"10.1109/ICIST52614.2021.9440647","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440647","url":null,"abstract":"The mechanism of spatio-temporal gene expression is significantly related to the interaction between the two regulatory elements on the DNA, enhancer and promoter. Identifying enhancer-promoter interactions that disrupt cell-specific gene expression and cause different human diseases remains to be a great challenge. To figure this out, we construct a sequence-based deep learning model, Enhancer-Promoter interactions prediction network, briefly called the EPnet which accurately predicts the interaction between enhancer and promoter with given DNA sequences. The method we proposed requires no genomic data which makes it convenient to make predictions. Comparison with other existing methods and application on predicting interactions show that our method is of superior performance in multiple cell lines which proves that our model is trustworthy and robust.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124472824","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
Down-Level Control Based on Level Prediction of Landslide Evolutionary State 基于滑坡演化状态水平预测的下行控制
2021 11th International Conference on Information Science and Technology (ICIST) Pub Date : 2021-05-21 DOI: 10.1109/ICIST52614.2021.9440637
Shu Sun, Cheng Lian, Xiaoping Wang
{"title":"Down-Level Control Based on Level Prediction of Landslide Evolutionary State","authors":"Shu Sun, Cheng Lian, Xiaoping Wang","doi":"10.1109/ICIST52614.2021.9440637","DOIUrl":"https://doi.org/10.1109/ICIST52614.2021.9440637","url":null,"abstract":"Accurate prediction and effective control are the key to reducing the impact of landslide disasters. In practice, most of recent studies focus on landslide displacement prediction and control. In this paper, we propose a new control method based on the level prediction of landslide evolution state, namely down-level control. The core components are level predictor and interval predictor in this method. Specially, we first transform the traditional displacement regression prediction problem into a level classification prediction problem by labeling discrete category information for landslide sample points. Then the level predictor based on Multi-task learning-Stacked long-short time memory network (MTL-SLSTM) is established to predict the state of the landslide and judge whether the system needs to be controlled. Finally, we design a safe rainfall interval predictor based on bootstrap method to obtain the safe value of control variation. The effectiveness of the proposed control method is verified on Baishuihe and Shiliushubao landslides. The results show the proposed down-level control method is valid and more intuitive.","PeriodicalId":371599,"journal":{"name":"2021 11th International Conference on Information Science and Technology (ICIST)","volume":"71 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116281705","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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