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A PI+R Control Scheme Based on Multi-Agent Systems for Economic Dispatch in Isolated BESSs

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IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2154-2165页

作者： Yalin Zhang Zhongxin Liu Zengqiang Chen College of artificial intelligence Nankai UniversityTianjin 300350 Tianjin Key laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation Nankai UniversityTianjin 300350China IEEE

Battery energy storage systems(BESSs)are widely used in smart ***,power consumed by inner impedance and the capacity degradation of each battery unit become particularly severe,which has resulted in an increase in operating *** general economic dispatch(ED)algorithm based on marginal cost(MC)consensus is usually a proportional(P)controller,which encounters the defects of slow convergence speed and low control *** order to solve the distributed ED problem of the isolated BESS network with excellent dynamic and steady-state performance,we attempt to design a proportional integral(PI)controller with a reset mechanism(PI+R)to asymptotically promote MC consensus and total power mismatch towards 0 in this *** be frank,the integral term in the PI controller is reset to 0 at an appropriate time when the proportional term undergoes a zero crossing,which accelerates convergence,improves control accuracy,and avoids *** eigenvalues of the system under a PI+R controller is well analyzed,ensuring the regularity of the system and enabling the reset *** ensure supply and demand balance within the isolated BESSs,a centralized reset mechanism is introduced,so that the controller is distributed in a flow set and centralized in a jump *** cope with Zeno behavior and input delay,a dwell time that the system resides in a flow set is *** on this,the system with input delays can be reduced to a time-delay free *** the capacity limitation of the battery,a modified MC scheme with PI+R controller is *** correctness of the designed scheme is verified through relevant simulations.

关键词： Battery energy storage system(BESS) distributed control economic dispatch multi-agent system reset control

Investigating Optical Transport Network Performance:A Recurrence Plot Approach

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China Communications 2024年第5期21卷 166-176页

作者： Sun Xiaochuan Cao Difei Wei Biao Li Zhigang Li Yingqi College of artificial intelligence North China University of Science and TechnologyTangshan 063210China Hebei Key laboratory of Industrial Intelligent Perception Tangshan 063210China

In future optical transport networks,lightpath performance analysis is of great practical significance for fully automated *** general,the quality of transmission(QoT)of lightpaths,measured by optical quality factor or optical signal-to-noise ratio,has a complex time-varying process,along with the interactions of the other lightpath state parameters(LSPs),such as transmit power,chromatic dispersion,polarization mode *** studies are mostly focused on lightpath QoT estimation,but ignoring lightpath-level data *** this case,our article proposes a novel lightpath performance analysis method considering recurrence plot(RP)and cross recurrence plot(CRP).Firstly,we give a detailed interpretation on the recurrence patterns of LSPs via a qualitative 2-D RP representation and its quantitative *** can potentially enable the accurate and fast lightpath failure detection with a low computational *** the other hand,CRP is devoted to modeling the relationships between lightpath QoT and LSPs,and the correlation degree is determined by a geometric mean of multiple indexes of cross recurrence quantification *** the view of application,such CRP analysis can provide the effective knowledge sharing to guarantee more credible QoT *** experiments on a real-world optical network dataset have clearly demonstrated the effectiveness of our proposal.

关键词： CRP analysis lightpath QoT optical transport networks RP analysis

Sequential Propagation of Chaos for Mean-Field BSDE Systems

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Chinese Annals of Mathematics,Series B 2024年第1期45卷 11-40页

作者： Xiaochen LI Kai DU Shanghai Center for Mathematical Sciences Fudan UniversityShanghai 200433China. Shanghai artificial intelligence laboratory 701 Yunjin RoadShanghai 200433China

A new class of backward particle systems with sequential interaction is proposed to approximate the mean-field backward stochastic differential *** is proven that the weighted empirical measure of this particle system converges to the law of the McKean-Vlasov system as the number of particles *** on the Wasserstein met-ric,quantitative propagation of chaos results are obtained for both linear and quadratic growth ***,numerical experiments are conducted to validate our theoretical results.

关键词： Backward propagation of chaos Particle system Sequential interaction McKean-Vlasov BSDE Convergence rate

Semantic-aware entity alignment for low resource language knowledge graph

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Frontiers of Computer Science 2024年第4期18卷 97-106页

作者： Junfei TANG Ran SONG Yuxin HUANG Shengxiang GAO Zhengtao YU Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China Yunnan Key laboratory of artificial intelligence Kunming University of Science and TechnologyKunming 650500China

Entity alignment(EA)is an important technique aiming to find the same real entity between two different source knowledge graphs(KGs).Current methods typically learn the embedding of entities for EA from the structure of KGs for *** EA models are designed for rich-resource languages,requiring sufficient resources such as a parallel corpus and pre-trained language ***,low-resource language KGs have received less attention,and current models demonstrate poor performance on those low-resource ***,researchers have fused relation information and attributes for entity representations to enhance the entity alignment performance,but the relation semantics are often *** address these issues,we propose a novel Semantic-aware Graph Neural Network(SGNN)for entity ***,we generate pseudo sentences according to the relation triples and produce representations using pre-trained ***,our approach explores semantic information from the connected relations by a graph neural *** model captures expanded feature information from *** results using three low-resource languages demonstrate that our proposed SGNN approach out performs better than state-of-the-art alignment methods on three proposed datasets and three public datasets.

关键词： graph neural network knowledge graph entity alignment low-resource language

Audio Mixing Inversion via Embodied Self-supervised Learning

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Machine intelligence Research 2024年第1期21卷 55-62页

作者： Haotian Zhou Feng Yu Xihong Wu Department of AI Music and Music Information Technology Central Conservatory of MusicBeijing 100031China laboratory of Music artificial intelligence Laboratory of Philosophy and Social SciencesMinistry of EducationBeijing 100031China School of intelligence Science and Technology Peking UniversityBeijing 100871China

Audio mixing is a crucial part of music *** analyzing or recreating audio mixing,it is of great importance to conduct research on estimating mixing parameters used to create mixdowns from music recordings,i.e.,audio mixing ***,approaches of audio mixing inversion are rarely explored.A method of estimating mixing parameters from raw tracks and a stereo mixdown via embodied self-supervised learning is *** this work,several commonly used audio effects including gain,pan,equalization,reverb,and compression,are taken into *** method is able to learn an inference neural network that takes a stereo mixdown and the raw audio sources as input and estimate mixing parameters used to create the mixdown by iteratively sampling and *** the sampling step,the inference network predicts a set of mixing parameters,which is sampled and fed to an audio-processing framework to generate audio data for the training *** the training step,the same network used in the sampling step is optimized with the sampled data generated from the sampling *** method is able to explicitly model the mixing process in an interpretable way instead of using a black-box neural network model.A set of objective measures are used for *** experimental results show that this method has better performance than current state-of-the-art methods.

关键词： Audio mixing inversion intelligent audio mixing self-supervised learning audio signal processing deep learning

Ensemble successor representations for task generalization in offline-to-online reinforcement learning

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Science China(Information Sciences) 2024年第7期67卷 240-255页

作者： Changhong WANG Xudong YU Chenjia BAI Qiaosheng ZHANG Zhen WANG Space Control and Inertial Technology Research Center Harbin Institute of Technology Shanghai artificial intelligence laboratory Shenzhen Research Institute of Northwestern Polytechnical University School of Cybersecurity Northwestern Polytechnical University

In reinforcement learning(RL), training a policy from scratch with online experiences can be inefficient because of the difficulties in exploration. Recently, offline RL provides a promising solution by giving an initialized offline policy, which can be refined through online interactions. However, existing approaches primarily perform offline and online learning in the same task, without considering the task generalization problem in offline-to-online adaptation. In real-world applications, it is common that we only have an offline dataset from a specific task while aiming for fast online-adaptation for several tasks. To address this problem, our work builds upon the investigation of successor representations for task generalization in online RL and extends the framework to incorporate offline-to-online learning. We demonstrate that the conventional paradigm using successor features cannot effectively utilize offline data and improve the performance for the new task by online fine-tuning. To mitigate this, we introduce a novel methodology that leverages offline data to acquire an ensemble of successor representations and subsequently constructs ensemble Q functions. This approach enables robust representation learning from datasets with different coverage and facilitates fast adaption of Q functions towards new tasks during the online fine-tuning *** empirical evaluations provide compelling evidence showcasing the superior performance of our method in generalizing to diverse or even unseen tasks.

关键词： offline reinforcement learning online fine-tuning task generalization successor representations ensembles

Sparse convolutional model with semantic expression for waste electrical appliances recognition

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Science China(Technological Sciences) 2024年第9期67卷 2881-2893页

作者： HAN HongGui LIU YiMing LI FangYu DU YongPing Faculty of Information Technology Beijing University of TechnologyBeijing 100124China Beijing Key laboratory of Computational intelligence and Intelligent System Beijing 100124China Engineering Research Center of Digital Community Ministry of EducationBeijing 100124China Beijing artificial intelligence Institute and Beijing laboratory for Intelligent Environmental Protection Beijing 100124China

Deep neural networks play an important role in the recognition of waste electrical appliances. However, deep neural network components still lack reliability in decision-making features. To address this problem, a sparse convolutional model with semantic expression(SCMSE) is proposed. First, a low-rank sparse semantic expression component, combining the benefits of residual networks and sparse representation, is adapted to enhance sparse feature extraction and semantic expression. Second, a reliable network architecture is obtained by iterating the optimal sparse solution, enhancing semantic expression. Finally, the results of visualization experiments on the waste electrical appliances dataset demonstrate that the proposed SCMSE can obtain excellent semantic performance.

关键词： sparse convolutional model deep neural network semantic expression visualization computer vision

BMLP:behavior-aware MLP for heterogeneous sequential recommendation

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Frontiers of Computer Science 2024年第3期18卷 235-237页

作者： Weixin LI Yuhao WU Yang LIU Weike PAN Zhong MING College of Computer Science and Software Engineering Shenzhen UniversityShenzhen 518060China Guangdong laboratory of artificial intelligence and Digital Economy(SZ) Shenzhen 518123China

1 Introduction Recommender systems can effectively alleviate the problem of information ***,traditional recommendation methods cannot capture users’dynamic *** recommendation methods model user sequences to obtain more accurate and dynamic user ***,deep learning-based sequential recommendation methods have achieved great *** is proposed to capture the sequential information[1,2].Attention-based methods[3]use attention mechanisms to learn relationships between ***-based methods[4−6]transform sequences into graph structures to capture relationships of ***,they have the following two limitations.

关键词： sequences behavior sequential

Flexible,high-density,laminated ECoG electrode array for high spatiotemporal resolution foci diagnostic localization of refractory epilepsy

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Bio-Design and Manufacturing 2024年第4期7卷 388-398页

作者： Yafeng Liu Zhouheng Wang Yang Jiao Ying Chen Guangyuan Xu Yinji Ma Xue Feng Applied Mechanics laboratory Department of Engineering MechanicsTsinghua UniversityBeijing 100084China laboratory of Flexible Electronics Technology Tsinghua UniversityBeijing 100084China College of artificial intelligence Southwest UniversityChongqing 400715China Institute of Flexible Electronics Technology of THU Jiaxing 314000China Qiantang Science and Technology Innovation Center Hangzhou 310016China School of artificial intelligence Beijing University of Posts and TelecommunicationsBeijing 100876China

High spatiotemporal resolution brain electrical signals are critical for basic neuroscience research and high-precision focus diagnostic localization,as the spatial scale of some pathologic signals is at the submillimeter or micrometer *** entails connecting hundreds or thousands of electrode wires on a limited *** study reported a class of flexible,ultrathin,highdensity electrocorticogram(ECoG)electrode *** challenge of a large number of wiring arrangements was overcome by a laminated structure design and processing technology *** flexible,ultrathin,high-density ECoG electrode array was conformably attached to the cortex for reliable,high spatial resolution electrophysiologic *** minimum spacing between electrodes was 15μm,comparable to the diameter of a single *** hundred electrodes were prepared with an electrode density of 4444 mm^(-2).In focal epilepsy surgery,the flexible,high-density,laminated ECoG electrode array with 36 electrodes was applied to collect epileptic spike waves inrabbits,improving the positioning accuracy of epilepsy lesions from the centimeter to the submillimeter *** flexible,high-density,laminated ECoG electrode array has potential clinical applications in intractable epilepsy and other neurologic diseases requiring high-precision electroencephalogram acquisition.

关键词： Electrocorticogram(ECoG)electrode Epilepsy High density High resolution Laminated structure