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Congress on Evolutionary Computation

作者： Hao Hao Aimin Zhou Hu Zhang Shanghai Key Laboratory of Multidimensional Information Processing School of Computer Science and Technology East China Normal University Shanghai China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-mechanical Engineering Institute Beijing China

Preselection is an important strategy to improve evolutionary algorithms’ performance by filtering out unpromising solutions before fitness evaluations. This paper introduces a pre-selection strategy based on an approximated Pareto domination relationship for multiobjective evolutionary optimization. For each objective, a binary relation between each pair of solutions is constructed based on the current population, and a binary classifier is built based on the binary relation pairs. In this way, an approximated Pareto domination relationship can be defined. When new trial solutions are generated, the approximated Pareto domination is used to select promising solutions, which shall be evaluated by the real objective functions. The new preselection is integrated into two algorithms. The experimental results on two benchmark test suites suggest that the algorithms with preselection outperform their original ones.

关键词： Filtering Computational modeling Sociology Training data Evolutionary computation Approximation algorithms Linear programming

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Temperature prediction of generator carbon brush based on LSTM neural network

Temperature prediction of generator carbon brush based on LS...

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2021 China Automation Congress, CAC 2021

作者： Zhang, Qing Jiao, Tingyang Ma, Yinxing Zhang, Youmin Wu, Xiaohui Wu, Pengyue Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an710048 China The Faculty of Computing Science The University of Alberta EdmontonABT6G 2R3 Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi 'an University of Technology Xi'an710048 China Department of Mechanical Industrial and Aerospace Engineering Concordia University MontrealQCH3G 1M8 Canada Huaneng Weihai Power Generation Co. Ltd Weihai264200 China Xi 'an Thermal Power Research Institute Co. Ltd Xi'an710048 China

ISBN: (纸本)9781665426473

In order to improve the prediction accuracy of the carbon brush temperature trend of the generator, analyzing the operating state of the generator more accurately, and reduce other accidents like the unplanned outage caused by carbon brush failure of the generator in the power plant. A multi-step temperature prediction model based on the LSTM (Long Short-Term Memory) neural network is proposed. The data comes from real operating carbon brush temperature of Weihai Power Plant in ten days. Then the temperature prediction model is established to achieve an accurate prediction of the carbon brush temperature in the future day. The prediction error is stable within 0.4 °C. By comparing the predicted results of the BP model and Elman model, the error between the predicted results of each model and the actual temperature data is analyzed. By comparing the indicators and analyzing the actual curves, the results show that LSTM neural network has higher accuracy in predicting the temperature of generator carbon brush. This method is of reference significance for the accurate analysis of the operation state of the generator and the load analysis of the excitation system. © 2021 IEEE

关键词： Long short-term memory

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Insight into Reaction Performance and Product Formation in a Novel Coal Pyrolyzer of Pilot-Scale Test

SSRN

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SSRN 2023年

作者： Qian, Yanan An, Ping Jia, Xin Han, Zhennan Wu, Rongcheng Liu, Xiaoxing Xu, Guangwen State Key Laboratory of Chemical Safety SINOPEC Research Institute of Safety Engineering Co. Ltd. Qingdao266071 China Key Laboratory on Resources Chemicals and Materials of Ministry of Education of China Shenyang University of Chemical Technology Shenyang110142 China State Key Laboratory of Multiphase Complex System Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China Graduate School of Science and Technology China College of Chemical Engineering China

The pyrolysis behavior of coal in a pilot-scale moving bed with internals is modeled through computational fluid dynamics (CFD) simulations. The temperature field, reaction field, volatile flow paths inside the reactor, and effects of the internal design and operating parameters on the tar yield are systematically investigated. The simulation results show that the central gas channel allows the majority of generated volatiles to laterally pass through the low-temperature bed layer. This not only enhanced the primary volatile generation reaction but also significantly reduced the secondary cracking of tar. However, the placement of the heat transfer plates had a dual effect. While the plates significantly enhanced heat transfer, thereby promoting primary reactions, they could cause the volatiles to bend towards the high-temperature zone near the plates, resulting in the partial loss of tar. The tar yield may decrease with an increase in the number or area of heat transfer plates. Furthermore, investigations into the operational parameters revealed that increasing the furnace temperature appropriately and reducing the mass flux of coal were favorable for the heat transfer and yield increase in tar. © 2023, The Authors. All rights reserved.

关键词： Computational fluid dynamics

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Regional Geomagnetic Map Construction based on Support Vector Machine Residual Kriging

Regional Geomagnetic Map Construction based on Support Vecto...

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第三十九届中国控制会议

作者： Tong Liu Xingyu Li Mengyin Fu Zhaoxiang Liang Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Nanjing University of Science and Technology

Regional geomagnetic maps are widely used in geomagnetic navigation and magnetic anomaly detection. However,the complexity of geomagnetic spatial trend changes and the spatial sparseness of the geomagnetic data affect the accuracy of regional geomagnetic map construction. In order to improve the accuracy of regional geomagnetic maps, this paper proposes the Support Vector Machine Residual Kriging method（SVMRKriging）. First, Support Vector Machine（SVM） is used to fit the geomagnetic trend changes, then the residual component is interpolated by ordinary Kriging, and finally these two parts are added to construct a regional geomagnetic map. Experiments were performed using geomagnetic grid data and aeromagnetic data. The experiment results show that SVMRKriging method can improve the accuracy of regional geomagnetic maps with geomagnetic trend changes.

关键词： Regional Geomagnetic Map Kriging Support Vector Machine

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Answer Extraction with Graph Attention Network for Knowledge Graph Question Answering

Answer Extraction with Graph Attention Network for Knowledge...

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International Conference on Computer and Communications (ICCC)

作者： Jie Zhang Zhongmin Pei Wei Xiong Zhangkai Luo Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (数字)9781728186351

ISBN: (纸本)9781728186368

In the knowledge graph question answering, the graph neural network can be used to encode the subgraph nodes related to the question entity to select the correct answer node. However, existing researches mainly focus on the modalities for the node encoding with graph neural network, ignoring that different types of subgraphs have different requirements for encoding information. To overcome the problem, this paper divides the subgraph into two types: the searching graph and the extending graph. Then we propose an answer extraction method with graph attention network for the searching graph, which can weight the information of neighbor nodes with different attention instead of the average. The hierarchical attention is also introduced to integrate question information into the subgraph node embedding to obtain the node presentation with question dependency. The accuracy of 48.2% is achieved on the CommonsenseQA dataset, which is much higher than the random guess (20%). In addition, the accuracy of the simplified model with no hierarchical attention decreases by 3.5%, which indicates the hierarchical attention mechanism can improve the predictive performance of the proposed model.

关键词： Computational modeling Predictive models Knowledge discovery Search problems Graph neural networks Encoding Task analysis

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Recent Few-Shot Object Detection Algorithms: A Survey with Performance Comparison

arXiv

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arXiv 2022年

作者： Liu, Tianying Zhang, Lu Wang, Yang Guan, Jihong Fu, Yanwei Zhao, Jiajia Zhou, Shuigeng Department of Computer Science and Technology Tongji University Shanghai201804 China The Project Management Office of China National Scientific Seafloor Observatory Tongji University Shanghai200092 China Shanghai Key Lab of Intelligent Information Processing The School of Computer Science Fudan University Shanghai200438 China Shanghai Key Lab of Intelligent Information Processing The School of Data Science Fudan University Shanghai200433 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

The generic object detection (GOD) task has been successfully tackled by recent deep neural networks, trained by an avalanche of annotated training samples from some common classes. However, it is still non-trivial to generalize these object detectors to the novel long-tailed object classes, which have only few labeled training samples. To this end, the Few-Shot Object Detection (FSOD) has been topical recently, as it mimics the humans' ability of learning to learn, and intelligently transfers the learned generic object knowledge from the common heavy-tailed, to the novel long-tailed object classes. Especially, the research in this emerging field has been flourishing in recent years with various benchmarks, backbones, and methodologies proposed. To review these FSOD works, there are several insightful FSOD survey articles [58, 59, 74, 78] that systematically study and compare them as the groups of fine-tuning/transfer learning, and meta-learning methods. In contrast, we review the existing FSOD algorithms from a new perspective under a new taxonomy based on their contributions, i.e., data-oriented, model-oriented, and algorithm-oriented. Thus, a comprehensive survey with performance comparison is conducted on recent achievements of FSOD. Furthermore, we also analyze the technical challenges, the merits and demerits of these methods, and envision the future directions of FSOD. Specifically, we give an overview of FSOD, including the problem definition, common datasets, and evaluation protocols. The taxonomy is then proposed that groups FSOD methods into three types. Following this taxonomy, we provide a systematic review of the advances in FSOD. Finally, further discussions on performance, challenges, and future directions are presented. Copyright © 2022, The Authors. All rights reserved.

关键词： Object detection

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Directional polarization modulation for secure dual-polarized satellite communication

Directional polarization modulation for secure dual-polarize...

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2019 International Conference on Communications, Information system, and Computer Engineering, CISCE 2019

作者： Luo, Zhangkai Pei, Zhongmin Zou, Bo Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing China

ISBN: (纸本)9781728136813

This paper proposes a directional polarization modulation method to enhance the transmission security in dual-polarized satellite communications. Indeed, two components of the polarized signal are respectively transmitted by two orthogonally polarized beams, which are formed by a dual-polarized array. Subsequently, a deviation angle is designed, which is used to determine the difference between the desired direction and the direction of the polarized beams. With a positive deviation angle, two polarized beams point to different directions. In this manner, only in the desired direction that two beam gains equal to each other, the polarized signals can be demodulated accurately, while the constellation is distorted in undesired directions, which makes it difficult to recover the information and, thus the transmission security is enhanced. Theoretical analysis and simulation results demonstrate the security performance of the proposed method. © 2019 IEEE.

关键词： Satellites

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Editorial

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International Journal of Innovative Computing and Applications 2019年第1期10卷 1-2页

作者： Cui, Zhihua Gao, Xiao-Zhi Complex System and Computational Intelligence Laboratory Taiyuan University of Science and Technology 030024 China School of Computing University of Eastern Finland Kuopio70210 Finland

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Ag_(3)PO_(4) decorated black urchin-like defective TiO_(2) for rapid and long-term bacteria-killing under visible light

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Bioactive Materials 2021年第6期6卷 1575-1587页

作者： Yingde Xu Xiangmei Liu Yufeng Zheng Changyi Li Kelvin Wai Kwok Yeung Zhenduo Cui Yanqin Liang Zhaoyang Li Shengli Zhu Shuilin Wu School of Materials Science&Engineering The Key Laboratory of Advanced Ceramics and Machining Technology By the Ministry of Education of ChinaTianjin UniversityTianjin300072China Hubei Key Laboratory of Polymer Materials Ministry-of-Education Key Laboratory for the Green Preparation and Application of Functional MaterialsSchool of Materials Science&EngineeringHubei UniversityWuhan430062China College of Engineering State Key Laboratory for Turbulence and Complex SystemDepartment of Materials Science and EngineeringPeking UniversityBeijing100871China Stomatological Hospital Tianjin Medical UniversityTianjin300070China Department of Orthopaedics&Traumatology Li Ka Shing Faculty of MedicineThe University of Hong KongPokfulamHong Kong999077China

Both phototherapy via photocatalysts and physical puncture by artificial nanostructures are promising substitutes for antibiotics when treating drug-resistant bacterial infectious ***,the photodynamic therapeutic efficacy of photocatalysts is seriously restricted by the rapid recombination of photogenerated electron-hole ***,the nanostructures of physical puncture are limited to two-dimensional(2D)platforms,and they cannot be fully used ***,this research developed a synergistic system of Ag_(3)PO_(4) nanoparticles(NPs),decorated with black urchin-like defective TiO_(2)(BU-TiO_(2-X)/Ag_(3)PO_(4)).These NPs had a decreased bandgap compared to BU-TiO_(2-X),and BU-TiO_(2)-X/Ag_(3)PO_(4)(3:1)exhibited the lowest bandgap and the highest separation efficiency for photogenerated electron-hole *** combination with BU-TiO_(2-X),the photostability of Ag_(3)PO_(4) improved because the oxygen vacancy of BU-TiO_(2-X) retards the reduction of Ag^(+) in Ag_(3)PO_(4) into Ag^(0),thus reducing its *** addition,the nanospikes on the surface of BU-TiO_(2-X) can,from all directions,physically puncture bacterial cells,thus assisting the hybrid’s photodynamic therapeutic effects,alongside the small amount of Ag^(+) released from Ag_(3)PO_(4).This achieves synergy,endowing the hybrid with high antibacterial efficacy of 99.76±0.15%and 99.85±0.09%against Escherichia coli and Staphylococcus aureus,respectively,after light irradiation for 20 min followed by darkness for 12 *** is anticipated that these findings may bring new insight for developing synergistic treatment strategies against bacterial infectious diseases or pathogenic bacterial polluted environments.

关键词： Antibacterial Ag_(3)PO_(4) Defective TiO_(2) Photocatalytic Puncture

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Bayesian Optimization Framework for Efficient Fleet Design in Autonomous Multi-Robot Exploration

arXiv

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arXiv 2024年

作者： Concha, David Molina Li, Jiping Yin, Haoran Park, Kyeonghyeon Lee, Hyun-Rok Lee, Taesik Sirohi, Dhruv Lee, Chi-Guhn The Dynamic Optimization and Reinforcement Learning Laboratory The Department of Mechanical & Industrial Engineering University of Toronto TorontoONM5S3G8 Canada The Department of Electrical & Computer Engineering University of Toronto TorontoONM5S3G8 Canada The Division of Engineering Science The Faculty of Applied Science and Engineering University of Toronto TorontoONM5S3G8 Canada The Complex System Design Laboratory The Department of Industrial and Systems Engineering Korea Advanced Institute of Science and Technology Daejeon34141 Korea Republic of The Department of Industrial Engineering Inha University Incheon22212 Korea Republic of

This study addresses the challenge of fleet design optimization in the context of heterogeneous multi-robot fleets, aiming to obtain feasible designs that balance performance and costs. In the domain of autonomous multi-robot exploration, reinforcement learning agents play a central role, offering adaptability to complex terrains and facilitating collaboration among robots. However, modifying the fleet composition results in changes in the learned behavior, and training multi-robot systems using multi-agent reinforcement learning is expensive. Therefore, an exhaustive evaluation of each potential fleet design is infeasible. To tackle these hurdles, we introduce Bayesian Optimization for Fleet Design (BOFD), a framework leveraging multiobjective Bayesian Optimization to explore fleets on the Pareto front of performance and cost while accounting for uncertainty in the design space. Moreover, we establish a sub-linear bound for cumulative regret, supporting BOFD’s robustness and efficacy. Extensive benchmark experiments in synthetic and simulated environments demonstrate the superiority of our framework over state-of-the-art methods, achieving efficient fleet designs with minimal fleet evaluations. Copyright © 2024, The Authors. All rights reserved.

关键词： Multipurpose robots

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