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Improved Segmented Belief Propagation List Decoding for Polar Codes with Bit-Flipping

China Communications 2024年第3期21卷 19-36页

作者： Mao Yinyou Yang dong liu Xingcheng Zou En School of Electronics and Information Technology(SEIT) Sun Yat-sen University(SYSU)Guangzhou 510006China School of Information Science Guangzhou Xinhua UniversityGuangzhou 510520China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519080China

Belief propagation list(BPL) decoding for polar codes has attracted more attention due to its inherent parallel nature. However, a large gap still exists with CRC-aided SCL(CA-SCL) *** this work, an improved segmented belief propagation list decoding based on bit flipping(SBPL-BF) is proposed. On the one hand, the proposed algorithm makes use of the cooperative characteristic in BPL decoding such that the codeword is decoded in different BP decoders. Based on this characteristic, the unreliable bits for flipping could be split into multiple subblocks and could be flipped in different decoders simultaneously. On the other hand, a more flexible and effective processing strategy for the priori information of the unfrozen bits that do not need to be flipped is designed to improve the decoding convergence. In addition, this is the first proposal in BPL decoding which jointly optimizes the bit flipping of the information bits and the code bits. In particular, for bit flipping of the code bits, a H-matrix aided bit-flipping algorithm is designed to enhance the accuracy in identifying erroneous code bits. The simulation results show that the proposed algorithm significantly improves the errorcorrection performance of BPL decoding for medium and long codes. It is more than 0.25 d B better than the state-of-the-art BPL decoding at a block error rate(BLER) of 10^(-5), and outperforms CA-SCL decoding in the low signal-to-noise(SNR) region for(1024, 0.5)polar codes.

关键词： belief propagation list(BPL)decoding bit-flipping polar codes segmented CRC

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A Neural-network-based Alternative Scheme to Include Nonhydrostatic Processes in an Atmospheric Dynamical Core

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Advances in Atmospheric Sciences 2024年第6期41卷 1083-1099,I0002,I0003页

作者： Yang XIA Bin WANG Lijuan LI Li liu Jianghao LI Li dong Shiming XU Yiyuan LI Wenwen XIA Wenyu HUANG Juanjuan liu yong WANG Hongbo liu Ye PU Yujun HE Kun XIA Ministry of Education Key Laboratory for Earth System Modeling and Department of Earth System ScienceTsinghua UniversityBeijing 100084China State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Innovation Group 311020008 Southern Marine Science and Engineering Guangdong LaboratoryZhuhai 519000China Shanghai Ecological Forecasting and Remote Sensing Center Shanghai 200030China Key Laboratory of Earth System Modeling and Prediction China Meteorological AdministrationBeijing 100081China College of Ocean Sciences University of Chinese Academy of SciencesBeijing 100049China

Here,a nonhydrostatic alternative scheme(NAS)is proposed for the grey zone where the nonhydrostatic impact on the atmosphere is evident but not large enough to justify the necessity to include an implicit nonhydrostatic solver in an atmospheric dynamical *** NAS is designed to replace this solver,which can be incorporated into any hydrostatic models so that existing well-developed hydrostatic models can effectively serve for a longer *** advances in machine learning(ML)provide a potential tool for capturing the main complicated nonlinear-nonhydrostatic *** this study,an ML approach called a neural network(NN)was adopted to select leading input features and develop the *** NNs were trained and evaluated with 12-day simulation results of dry baroclinic-wave tests by the Weather Research and Forecasting(WRF)*** forward time difference of the nonhydrostatic tendency was used as the target variable,and the five selected features were the nonhydrostatic tendency at the last time step,and four hydrostatic variables at the current step including geopotential height,pressure in two different forms,and potential temperature,***,a practical NAS was developed with these features and trained layer by layer at a 20-km horizontal resolution,which can accurately reproduce the temporal variation and vertical distribution of the nonhydrostatic *** by the NN-based NAS,the improved hydrostatic solver at different horizontal resolutions can run stably for at least one month and effectively reduce most of the nonhydrostatic errors in terms of system bias,anomaly root-mean-square error,and the error of the wave spatial pattern,which proves the feasibility and superiority of this scheme.

关键词： neural network nonhydrostatic alternative scheme atmospheric model dynamical core

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Optimal Stochastic Scheduling Strategy of Multi-vector Energy Complex Integrated with Full-blown Power-to-biomethane Model

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Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 863-873页

作者： Guanwei Zeng Chengxi liu Minfang Liao yongjian Luo Xuzhu dong Hubei Engineering and Technology Research Center for AC/DC Intelligent Distribution Network WuhanChina the School of Electrical Engineering and Automation Wuhan UniversityWuhanChina

We propose an optimal stochastic scheduling strategy for a multi-vector energy complex(MEC),considering a fullblown model of the power-to-biomethane(Pt M)*** conventional optimization that uses a simple efficiency coefficient to coarsely model energy conversion between electricity and biomethane,a detailed Pt M model is introduced to emphasize the reactor kinetics and chemical equilibria of *** model crystallizes the interactions between the Pt M process and MEC flexibility,allowing to adjust the operating condition of the methanation reactor for optimal MEC operation in stochastic *** optimization and flowsheet design of the Pt M process increase the average selectivity of methane(i.e.,ratio between net biomethane production and hydrogen consumption)up to 83.7%in the proposed synthesis *** results can provide information and predictions to operators about the optimal operating conditions of a Pt M unit while improving the MEC flexibility.

关键词： Multi-vector energy complex optimal stochastic scheduling power-to-biomethane unit process synthesis natural gas

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Anomaly-Resistant Decentralized State Estimation Under Minimum Error Entropy With Fiducial Points for Wide-Area Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 74-87页

作者： Bogang Qu Zidong Wang Bo Shen Hongli dong Hongjian liu the College of Automation Engineering Shanghai University of Electric PowerShanghai 200090China IEEE the Department of Computer Science Brunel University LondonUxbridgeMiddiesex UB83PHUK the College of Information Science and Technology Donghua UniversityShanghai 200051 the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China the Artificial Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 the Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast PetroleumDaqing 163318 the Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China the Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of EducationAnhui Polytechnic UniversityWuhu 2410000 the School of Mathematics and Physics Anhui Polytechnic UniversityWuhu 241000China

This paper investigates the anomaly-resistant decentralized state estimation(SE) problem for a class of wide-area power systems which are divided into several non-overlapping areas connected through transmission lines. Two classes of measurements(i.e., local measurements and edge measurements) are obtained, respectively, from the individual area and the transmission lines. A decentralized state estimator, whose performance is resistant against measurement with anomalies, is designed based on the minimum error entropy with fiducial points(MEEF) criterion. Specifically, 1) An augmented model, which incorporates the local prediction and local measurement, is developed by resorting to the unscented transformation approach and the statistical linearization approach;2) Using the augmented model, an MEEF-based cost function is designed that reflects the local prediction errors of the state and the measurement;and 3) The local estimate is first obtained by minimizing the MEEF-based cost function through a fixed-point iteration and then updated by using the edge measuring information. Finally, simulation experiments with three scenarios are carried out on the IEEE 14-bus system to illustrate the validity of the proposed anomaly-resistant decentralized SE scheme.

关键词： Decentralized state estimation(SE) measurements with anomalies minimum error entropy unscented Kalman filter wide-area power systems

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A benchmark-based method for evaluating hyperparameter optimization techniques of neural networks for surface water quality prediction

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Frontiers of Environmental Science & Engineering 2024年第5期18卷 13-27页

作者： Xuan Wang Yan dong Jing Yang Zhipeng liu Jinsuo Lu School of Environmental and Municipal Engineering Xi’an University of Architecture and TechnologyXi’an710055China Shaanxi Key Laboratory of Environmental Engineering Xi’an University of Architecture and TechnologyXi’an710055China State Key Laboratory of Green Building in West China Xi’an University of Architecture and TechnologyXi’an710055China

Neural networks(NNs)have been used extensively in surface water prediction tasks due to computing algorithm improvements and data *** essential step in developing an NN is the hyperparameter *** practice,it is common to manually determine hyperparameters in the studies of NNs in water resources *** may result in considerable randomness and require significant computation time;therefore,hyperparameter optimization(HPO)is *** study adopted five representatives of the HPO techniques in the surface water quality prediction tasks,including the grid sampling(GS),random search(RS),genetic algorithm(GA),Bayesian optimization(BO)based on the Gaussian process(GP),and the tree Parzen estimator(TPE).For the evaluation of these techniques,this study proposed a method:first,the optimal hyperparameter value sets achieved by GS were regarded as the benchmark;then,the other HPO techniques were evaluated and compared with the benchmark in convergence,optimization orientation,and consistency of the optimized *** results indicated that the TPE-based BO algorithm was recommended because it yielded stable convergence,reasonable optimization orientation,and the highest consistency rates with the benchmark *** optimization consistency rates via TPE for the hyperparameters hidden layers,hidden dimension,learning rate,and batch size were 86.7%,73.3%,73.3%,and 80.0%,*** the evaluation of HPO techniques directly based on the prediction performance of the optimized NN in a single HPO test,the proposed benchmark-based HPO evaluation approach is feasible and robust.

关键词： Neural networks Hyperparameter optimization Surface water quality prediction Bayes optimization Genetic algorithm

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Discovering Latent Variables for the Tasks With Confounders in Multi-Agent Reinforcement Learning

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IEEE/CAA Journal of Automatica Sinica 2024年第7期11卷 1591-1604页

作者： Kun Jiang Wenzhang liu Yuanda Wang Lu dong Changyin Sun the School of Automation Southeast UniversityNanjing 210096China the School of Artificial Intelligence Anhui UniversityHefei 230601China IEEE the School of Cyber Science and Engineering Southeast UniversityNanjing 211189China the Engineering Research Center of Autonomous Unmanned System Technology Ministry of EducationHefei 230601China

Efficient exploration in complex coordination tasks has been considered a challenging problem in multi-agent reinforcement learning(MARL). It is significantly more difficult for those tasks with latent variables that agents cannot directly observe. However, most of the existing latent variable discovery methods lack a clear representation of latent variables and an effective evaluation of the influence of latent variables on the agent. In this paper, we propose a new MARL algorithm based on the soft actor-critic method for complex continuous control tasks with confounders. It is called the multi-agent soft actor-critic with latent variable(MASAC-LV) algorithm, which uses variational inference theory to infer the compact latent variables representation space from a large amount of offline ***, we derive the counterfactual policy whose input has no latent variables and quantify the difference between the actual policy and the counterfactual policy via a distance function. This quantified difference is considered an intrinsic motivation that gives additional rewards based on how much the latent variable affects each agent. The proposed algorithm is evaluated on two collaboration tasks with confounders, and the experimental results demonstrate the effectiveness of MASAC-LV compared to other baseline algorithms.

关键词： Latent variable model maximum entropy multi-agent reinforcement learning(MARL) multi-agent system

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Data and Model Driven Task Offloading Strategy in the Dynamic Mobile Edge Computing System

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Journal of Systems Science & Complexity 2024年第1期37卷 351-368页

作者： dong Hairong WU Wei SONG Haifeng liu Zhen ZHANG Zixuan School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China School of Electronic and Information Engineering BeiHang UniversityBeijing 100191China CRSC Research&Design Institute Group Co. Ltd.Beijing 100070China

Mobile Edge Computing(MEC)provides communication and computational capabilities for the industrial Internet,meeting the demands of latency-sensitive ***,traditional model-driven task offloading strategies face challenges in adapting to situations with unknown network communication status and computational *** limitation becomes notably significant in complex industrial networks of high-speed *** by these considerations,a data and model-driven task offloading problem is proposed in this paper.A redundant communication network is designed to adapt to anomalous channel states when tasks are offloaded to edge *** link switching mechanism is executed by the train according to the attributes of the completed *** task offloading optimization problem is formulated by introducing data-driven prediction of communication states into the traditional ***,the optimal strategy is achieved by employing the informer-based prediction algorithm and the quantum particle swarm optimization method,which effectively tackle real-time optimization problems due to their low time *** simulations illustrate that the data and model-driven task offloading strategy can predict the communication state in advance,thus reducing the cost of the system and improving its robustness.

关键词： Data driven model informer mobile edge computing quantum particle swarm optimization task offloading.

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Comparison of Direct Pore-Scale and Volume-Averaging Methods for the Performance Evaluation of Porous Volumetric Solar Receiver

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Journal of Thermal Science 2024年第5期33卷 1607-1617页

作者： DU Shen HE Yaling LI dong liu Zhanbin LI Mengjie National Innovation Platform(Center)for Industry-Education Integration of Energy Storage Technology Key Laboratory of Thermo-Fluid Science and Engineering of Ministry of EducationXi’an Jiaotong UniversityXi’an710049China

Direct pore-scale and volume-averaging numerical simulations are two methods for investigating the performance of porous volumetric solar *** clarify the difference in the prediction of heat transfer processes,a direct comparison between these two methods was conducted at both steady state and transient *** numerical models were established based on X-ray computed tomography scans and a local thermal non-equilibrium model,*** empirical parameters,which are indispensable to the volume-averaging simulation,were determined by Monte Carlo ray tracing and direct pore-scale numerical *** predicted outlet air temperature of the receiver by the volume-averaging simulation method corresponded satisfactorily to that in the direct pore-scale *** largest discrepancies were observed when the receiver's working temperature was elevated,with differences of 5.5%and 3.68%for the steady state and transient state simulations,***,the volume-averaging method is incapable of capturing the local temperature information of the air and porous *** underestimates the inlet temperature of the receiver,leading to an overestimation of the receiver's thermal efficiency,with the largest difference being 6.51%.The comparison results show that the volume-averaging model is a good approximation to the pore-scale model when the empirical parameters are carefully selected.

关键词： porous media volumetric solar receiver pore-scale method volume-averaging method thermal performance

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Directional amine-based solvent extraction for simultaneous enhanced water recovery,salt separation and effective descaling from hypersaline brines

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Frontiers of Environmental Science & Engineering 2024年第3期18卷 83-92页

作者： Yuyao Zhang Litao Jia Jin Zhao Xuming liu Shuyu dong Chuanyang liu Yuanyuan Cui Shougang Research Institute of Technology Beijing 100043China Research Center of Environmental Technology in Water Pollution Source Identification and Precise Supervision School of EnvironmentTsinghua UniversityBeijing 100084China

The feasibility of simultaneous water recovery,salt separation and effective descaling of hypersaline brine was investigated by diisopropylamine(DIPA)-based directional solvent extraction(DSE),using diluted/concentrated seawater with initial saline concentration range of 12–237 g/L at extraction temperatures of 5 and 15℃,*** water recovery shows an obvious boundary at saline concentration of 115 g/L under dual effect of specific water extraction efficiency and extraction *** Cl^(–) ion concentration in product water is in sharp contrast to the nearly complete removal of SO_(4)^(2–)and hardness ions,indicating that DIPA-based DSE process indeed achieved efficient separation and purification of Cl^(–) ion from hypersaline ***,the radical precipitation of Mg^(2+)and Ca^(2+)ions in form of Mg(OH)_(2)and CaCO_(3)demonstrates effective descaling potential,although it leads to more DIPA residues in dewatered raffinate than product ***,an exponential correlation between the Cl^(–) removal efficiency and specific water extraction efficiency further reveals the intrinsic relationship of water extraction process and transfer of Cl^(–) ion to the product ***,the study provides a novel approach for integrating the water recovery and separation of Cl^(–) ion from ultra-high-salinity brines with radical precipitation of Mg^(2+)and Ca^(2+) ions in one step.

关键词： Hypersaline brines Directional solvent extraction Salt separation Ca^(2+)and Mg^(2+)descaling

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Few-shot image recognition based on multi-scale features prototypical network

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High Technology Letters 2024年第3期30卷 280-289页

作者： liu Jiatong DUAN yong School of Information Science Engineering Shenyang University of TechnologyShenyang 110870P.R.China Shenyang Key Laboratory of Advanced Computing and Application Innovation Shenyang 110870P.R.China

In order to improve the model􀆳s capability in expressing features during few-shot learning,a multi-scale features prototypical network(MS-PN)algorithm is *** metric learning algo-rithm is employed to extract image features and project them into a feature space,thus evaluating the similarity between samples based on their relative distances within the metric *** sufficiently extract feature information from limited sample data and mitigate the impact of constrained data vol-ume,a multi-scale feature extraction network is presented to capture data features at various scales during the process of image feature ***,the position of the prototype is fine-tuned by assigning weights to data points to mitigate the influence of outliers on the *** loss function integrates contrastive loss and label-smoothing to bring similar data points closer and separate dissimilar data points within the metric *** evaluations are conducted on small-sample datasets mini-ImageNet and *** method in this paper can achieve higher classification ***,in the 5-way 1-shot experiment,classification accuracy reaches 50.13%and 66.79%respectively on these two ***,in the 5-way 5-shot ex-periment,accuracy of 66.79%and 85.91%are observed,respectively.

关键词： few-shot learning multi-scale feature prototypical network channel attention label-smoothing

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