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Comprehensive Evaluation Method for Traffic Flow Data Quality Based on Grey Correlation Analysis and Particle Swarm Optimization

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Journal of Systems Science and Systems Engineering 2024年第1期33卷 106-128页

作者： wei Ba Baojun Chen Qi li School of Automation and Electrical Engineering Dalian Jiaotong UniversityDalian116028China Faculty of Electronic Information and Electrical Engineering Dalian University of TechnologyDalian116023China

Nowadays,data are more and more used for intelligent modeling and prediction,and the comprehensive evaluation of data quality is getting more and more attention as a necessary means to measure whether the data are usable or ***,the comprehensive evaluation method of data quality mostly contains the subjective factors of the evaluator,so how to comprehensively and objectively evaluate the data has become a bottleneck that needs to be solved in the research of comprehensive evaluation *** order to evaluate the data more comprehensively,objectively and differentially,a novel comprehensive evaluation method based on particle swarm optimization(PSO)and grey correlation analysis(GCA)is presented in this *** first,an improved GCA evaluation model based on the technique for order preference by similarity to an ideal solution(TOPSIS)is ***,an objective function model of maximum difference of the comprehensive evaluation values is built,and the PSO algorithm is used to optimize the weights of the improved GCA evaluation model based on the objective function ***,the performance of the proposed method is investigated through parameter analysis.A performance comparison of traffic flow data is carried out,and the simulation results show that the maximum average difference between the evaluation results and its mean value(MDR)of the proposed comprehensive evaluation method is 33.2.%higher than that of TOPSIS-GCA,and 6.86%higher than that of *** proposed method has better differentiation than other methods,which means that it objectively and comprehensively evaluates the data from both the relevance and differentiation of the data,and the results more effectively reflect the differences in data quality,which will provide more effective data support for intelligent modeling,prediction and other applications.

关键词： Data quality comprehensive evaluation particle swarm optimization grey correlation analysis traffic flow data

The First Five Years of a Phase Theory for Complex Systems and Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1728-1743页

作者： Dan Wang wei Chen li Qiu Division of Decision and Control Systems KTH Royal Institute of TechnologyStockholm 10044Sweden Department of Mechanics and Engineering Science&the State Key Laboratory for Turbulence and Complex Systems Peking UniversityBeijing 100871China Hong Kong University of Science and Technology Hong KongChinaand also with the Southern University of Science and TechnologyShenzhen 518055China

In this paper,we review the development of a phase theory for systems and networks in its first five years,represented by a trilogy:Matrix phases and their properties;The MIMO LTI system phase response,its physical interpretations,the small phase theorem,and the sectored real lemma;The synchronization of a multi-agent network using phase *** the end,we also summarize a list of ongoing research on the phase theory and speculate what will happen in the next five years.

关键词： Consensus and synchronization matrix phases multi-agent systems phase theory sectored real lemma small phase theorem.

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Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

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Advances in Atmospheric Sciences 2024年第7期41卷 1326-1341页

作者： Lu li Yongjiu DAI Zhongwang wei wei SHANGGUAN Nan wei Yonggen ZHANG Qingliang li Xian-Xiang li School of Atmospheric Sciences Sun Yat-sen UniversityGuangzhou 510275China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Guangzhou 510275China Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Guangzhou 510275China Institute of Surface-Earth System Science School of Earth System ScienceTianjin UniversityTianjin 300072China College of Computer Science and Technology Changchun Normal UniversityChangchun 130123China

Accurate soil moisture(SM)prediction is critical for understanding hydrological ***-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface *** addition to PB models,deep learning(DL)models have been widely used in SM predictions ***,few pure DL models have notably high success rates due to lacking physical ***,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM *** this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM *** performances of the proposed hybrid models were investigated and compared with two existing hybrid *** results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid ***,the ensemble model performed best among all hybrid models at all forecast time scales and different soil *** is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day *** findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

关键词： soil moisture forecasting hybrid model deep learning ConvLSTM attention mechanism

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A Two-stage Service-oriented Task Offloading Framework with Edge-cloud Collaboration:A Game Theory Approach

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Journal of Systems Science and Systems Engineering 2024年第5期33卷 521-551页

作者： Shiyong li Wenzhe li Huan liu wei Sun School of Economics and Management Yanshan UniversityQinhuangdao 066004

With the fast development of Mobile Internet,data traffic generated by end devices is anticipated to witness substantial growth in the future ***,processing tasks locally will cause latency due to the limited resources of the end ***-cloud collaboration,an effective solution for latency-sensitive applications,is attracting greater attention from both industry and *** combines the advantages of the cloud center with abundant computing resources and edge nodes with low-latency *** this paper,we propose a two-stage task offloading framework with edge-cloud collaboration to assist end devices processing latency-sensitive tasks either on the edge servers or in the cloud *** for homogeneous task offloading,in the first stage,the competitive end devices offload tasks to the edge *** formulate the selfish task offloading problem among end devices as a potential *** the second stage,the edge nodes request resources from the cloud center to process end devices tasks due to their limited ***,we consider the heterogeneous task offloading problem and use intelligent optimization algorithm to obtain the optimal offloading *** results show that the service prices of edge nodes influence the decisions and task offloading costs of end *** also verify the intelligent optimization algorithm can achieve optimal performance with low complexity and fast convergence.

关键词： Edge-cloud collaboration task offloading potential game simulation annealing algorithm

Non-innocent partners:bias distribution between photoanodes and cathodes in photoelectrochemical overall water-splitting cells

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National Science Review 2024年第6期11卷 88-89页

作者： wei li Dunwei Wang Department of Chemistry Merkert Chemistry Center Boston College

Photoelectrochemical (PEC) overall water splitting (OWS) represents a highly promising strategy to directly harvest solar energy and store it in the form of fuels,offering unique benefits such as mitigating issues con...

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Dynamic Measurement of Intracellular pH Based on Bioluminescent Bacteria

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Chemical Research in Chinese Universities 2024年第2期40卷 287-292页

作者： li Yaohua WANG wei State Key Laboratory of Analytical Chemistry for life Science School of Chemistry and Chemical EngineeringChemBIC(Chemistry and Biomedicine Innovation Center)Nanjing UniversityNanjing210023P.R.China

Intracellular pH(pHi)is a fundamental indicator of cellular physiological state,regulating cellular state and function,and has important research *** various probes for measuring intracellular pH were available,it is challenging to reflect pHi in real-time and reversible ***,we developed a whole-cell bioluminescent(BL)probe based on wild type BL bacteria,photobacterium phosphoreum(***),to determine and image *** dependence of BL intensity of *** on pH values of culture solutions was *** was found that BL intensity could respond to the change of pH values rapidly and *** further revealed that *** maintained pH homeostasis in the extracellular pH(pHe)within the range of 5.0–7.0,while intracellular pH homeostasis was destroyed at the alkaline *** method opens up the enormous potential of BL bacteria as an alternative to fluorescence for monitoring and imaging pHi.

关键词： Bioluminescence P.phosphoreum Intracellular pH Cell imaging

Microstructure Evolution and Nanomechanical Behavior of Micro-Area in Molten Pool of Selective Laser Melting(CoCrNi)_(82.Al_(9)Ti_(9)High-Entropy Alloy

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Acta Metallurgica Sinica(English Letters) 2024年第6期37卷 1019-1033页

作者： Hong-wei Zhang li-wei Lan Zhe-Yu Yang Chang-Chun li Wen-Xian Wang College of Materials Science and Engineering Taiyuan University of TechnologyTaiyuan030024China Ministry of Education Key Laboratory of Interface Science and Engineering in Advanced MaterialsTaiyuan University of TechnologyTaiyuan030024China Shanxi-Zhejiang University New Materials and Chemical Research Institute Taiyuan030032China

In this work,the phase evolution mechanism and nanomechanical properties of(CoCrNi))(82.Al_(9)Ti_(9)high-entropy alloy(HEA)prepared by selective laser melting(SLM)in the molten pool were *** HEA contains multiple primary elements and undergoes high-temperature gradient and rapid cooling during *** leads to significant inhomogeneity of nano-scale microstructure characteristics and instability of *** optimizing process parameters,the microstructure evolution at the optimal parameter volume energy density of 440 J/mm^(3)was studied.A phase transition from BCC to FCC occurred in the melt *** the micro-area of the melt pool results in a temperature rise and the combustion-induced loss of Al ***,the Ni element content increases significantly outside the melt *** process enhances the phase stability of FCC and facilitates phase ***,rapid cooling leads to the formation of distinctive ultrafine equiaxial crystals inside the melt pool,accompanied by the generation of intracrystalline needle-like nano-scale *** the melt pool,the accumulation of energy results in the formation of coarse ***,the nano-hardness inside the molten pool is remarkably high at 11.79 GPa,while the outside the molten pool is reduced to 9.58 *** the fracture toughness outside the melt pool also *** with inside the melt pool,the residual stress outside the melt pool changed from compressive to tensile stress and decreased from 603.2. to 32..84 MPa.

关键词： High-entropy alloys Selective laser melting Microstructure evolution Nanoindentation

An improved deep dilated convolutional neural network for seismic facies interpretation

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Petroleum Science 2024年第3期21卷 1569-1583页

作者： Na-Xia Yang Guo-Fa li Ting-Hui li Dong-Feng Zhao wei-wei Gu State Key Laboratory of Petroleum Resources and Engineering CNPC Key Lab of Geophysical ExplorationChina University of Petroleum(Beijing)Beijing 102249China Dagang Branch Research InstituteBGPTianjin300280China

With the successful application and breakthrough of deep learning technology in image segmentation,there has been continuous development in the field of seismic facies interpretation using convolutional neural *** intelligent and automated methods significantly reduce manual labor,particularly in the laborious task of manually labeling seismic ***,the extensive demand for training data imposes limitations on their wider *** overcome this challenge,we adopt the UNet architecture as the foundational network structure for seismic facies classification,which has demonstrated effective segmentation results even with small-sample training ***,we integrate spatial pyramid pooling and dilated convolution modules into the network architecture to enhance the perception of spatial information across a broader *** seismic facies classification test on the public data from the F3 block verifies the superior performance of our proposed improved network structure in delineating seismic facies *** analysis against the traditional UNet model reveals that our method achieves more accurate predictive classification results,as evidenced by various evaluation metrics for image ***,the classification accuracy reaches an impressive 96%.Furthermore,the results of seismic facies classification in the seismic slice dimension provide further confirmation of the superior performance of our proposed method,which accurately defines the range of different seismic *** approach holds significant potential for analyzing geological patterns and extracting valuable depositional information.

关键词： Seismic facies interpretation Dilated convolution Spatial pyramid pooling Internal feature maps Compound loss function

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Engineering behaviour of in situ cored deep cement mixed marine deposits subjected to undrained and drained shearing

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第5期16卷 1749-1760页

作者： wei li Chung Yee Kwok Faculty of Engineering China University of GeosciencesWuhan430074China Department of Civil Engineering The University of Hong Kong999000Hong Kong SARChina

The deep cement mixing(DCM)is used to improve the capacity and reduce the settlement of the soft ground by forming cemented clay *** investigation on the mechanical behaviour of the DCM samples is limited to either laboratory-prepared samples or in-situ samples under unconfined *** this study,a series of drained and undrained triaxial shearing tests was performed on the in-situ cored DCM samples with high cement content to assess their mechanical *** is found that the drainage condition affects significantly the stiffness,peak and residual strengths of the DCM samples,which is mainly due to the state of excess pore water pressure at different strain levels,*** positive before the peak deviatoric stress and negative after the peak deviatoric stress,in the undrained *** slope of the failure envelope changes obviously with the confining pressures,being steeper at lower stress levels and flatter at higher stress *** strength parameters,effective cohesion and friction angle obtained from lower stress levels(c′0 andφ′0)are 400 kPa and 58°,respectively,which are deemed to be true for design in most DCM applications where the in-situ stress levels are normally at lower values of 50-2.0 ***,the computed tomography(CT)scanning system was adopted to visualize the internal structures of DCM *** is found that the clay pockets existing inside the DCM samples due to uneven mixing affect markedly their stress-strain behaviour,which is one of the main reasons for the high variability of the DCM samples.

关键词： Deep cement mixing(DCM) In-situ cored sample Triaxial shearing Drainage condition Confining pressure Computed tomography(CT)