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How Investor Sentiment Influences Stock Price Informativeness of Firms’Future Earnings:Evidence From China’s Stock Market 认领 引用
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作者 Junfeng Wang 《Journal of Sustainable Business and Economics》 2024年第4期1-32,共32页
This paper explores whether the level of stock price informativeness about listed companies’future earnings is influenced by investor sentiment.In prior studies,investor sentiment,which can be regarded as the mood of... This paper explores whether the level of stock price informativeness about listed companies’future earnings is influenced by investor sentiment.In prior studies,investor sentiment,which can be regarded as the mood of the market,is defined as a belief about unjustified firms’future cash flow,investment returns and risks in capital markets.At the same time,stock price informativeness indicates how much information about a firm’s future earnings is reflected by stock prices.Higher price informativeness indicates a higher market efficiency level.Using linear regression analysis based on panel data from China’s stock market and listed companies,this research documents how stock price informativeness can be reduced by investor sentiment during market pessimism.However,although the explanatory power of future earnings over stock returns is strengthened by positive sentiment,it is not certain that positive sentiment increases price informativeness since the asset price bubble exists with extreme market optimism.Furthermore,the effect of sentiment on price informativeness would be weakened by higher state-owned shareholding.These empirical results imply that sentiment,to a certain degree,causes the investors’ignorance during pessimism and exaggeration during optimism over firms’earning prospects.Moreover,investors usually lack favour for state-owned enterprises during optimism,even though these companies actually have considerable earning prospects.While during pessimism,which usually happens after a crisis,the profitability and reliability of these state-owned enterprises are again emphasised by investors. 展开更多
关键词 Sentiment Informativeness Stock market efficiency State-owned shareholding
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Research of Impact of Geografical Latitute and Residual Ionospheric Noises on Informativeness of Measuring of Zenith Wet Delay of GPS Signals 认领 引用
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作者 A. Sh. Mehdiyev R. A. Eminov +1 位作者 N. Y. Ismayilov H. H. Asadov 《Positioning》 2015年第3期44-48,共5页
It is noted that necessity of further increase of accuracy of GPS positioning systems requires de-velopment of more perfect methods to compensate information losses occurred due to residual ionospheric delay by using ... It is noted that necessity of further increase of accuracy of GPS positioning systems requires de-velopment of more perfect methods to compensate information losses occurred due to residual ionospheric delay by using optimization procedures. According to the conditions of formulated optimization task, the signaloise ratio in measurements of zenith wet delay depends on the second order ionospheric errors, geographic latitude and day of year. At the same time if we assume that the number of measurements at the fixed geographic site is proportional to geographic latitude and if we accept existence of only two antiphase scenarios for variation of residual ionospheric delay on latitude normed by their specific constant, there should be optimum functional dependence of precipitated water on latitude upon which the quantity of measuring information reaches the maximum. The mathematical grounding of solution of formulated optimization task is given. 展开更多
关键词 Zenith Wet Delay Information Optimization GPS Measurements Ionosphere Geographic Latitude
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Wireless Environmental Information Theory:A New Paradigm Toward 6G Online and Proactive Environment Intelligence Communication 认领 引用 被引量：4
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作者 Jianhua Zhang Li Yu +4 位作者 Shaoyi Liu Yichen Cai Yuxiang Zhang Hongbo Xing Tao Jiang 《Engineering》 SCIE EI CSCD 2026年第1期186-200,共15页
Channels are one of the five critical components of a communication system,and their ergodic capacity is based on all realizations of a statistical channel model.This statistical paradigm has successfully guided the d... Channels are one of the five critical components of a communication system,and their ergodic capacity is based on all realizations of a statistical channel model.This statistical paradigm has successfully guided the design of mobile communication systems from first generation(1G)to fifth generation(5G).However,this approach relies on offline channel measurements in specific environments,and thus,the system passively adapts to new environments,resulting in deviation from the optimal performance.As sixth generation(6G)expands into ubiquitous environments and pursues higher capacity,numerous sensing and artificial intelligence(AI)-based methods have emerged to combat random channel fading.However,there remains an urgent need for a proactive and online system design paradigm.From a system perspective,we propose an environment intelligence communication(EIC)based on wireless environmental information theory(WEIT)for 6G.The proposed EIC architecture operates in three steps.First,wireless environmental information(WEI)is acquired using sensing techniques.Then,leveraging WEI and channel data,AI techniques are employed to predict channel fading,thereby mitigating channel uncertainty.Finally,the communication system autonomously determines the optimal air-interface transmission strategy based on real-time channel predictions,enabling intelligent interaction with the physical environment.To make this attractive paradigm shift from theory to practice,we establish WEIT for the first time by answering three key problems:How should WEI be defined?Can it be quantified?Does it hold the same properties as statistical communication information?Subsequently,EIC aided by WEI(EIC-WEI)is validated across multiple air-interface tasks,including channel state information prediction,beam prediction,and radio resource management.Simulation results demonstrate that the proposed EIC-WEI significantly outperforms the statistical paradigm in decreasing overhead and performance optimization.Finally,several open problems and challenges,including regarding its accuracy,complexity,and generalization,are discussed.This work explores a novel and promising way for integrating communication,sensing,and AI capability in 6G. 展开更多
关键词 Sixth generation Intelligent communication Environment intelligence Wireless environmental information theory Environment sensing and reconstruction Channel prediction Digital twin channel ChannelGPT
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Dynamic decision-making of UAV swarm based on constrained multi-objective optimization under incomplete interference information 认领 引用 被引量：1
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作者 Kuixian LI Jinjie LIU +5 位作者 Xin GU Yandie YANG Cheng CHANG Haipeng CHEN Liangtian WAN Yun LIN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第7期64-77,共14页
The decision-making and resource allocation of UAV swarms play a crucial role in dynamic,uncertain environments.In such complex scenarios,UAV swarms need to effectively collaborate and communicate in frequently changi... The decision-making and resource allocation of UAV swarms play a crucial role in dynamic,uncertain environments.In such complex scenarios,UAV swarms need to effectively collaborate and communicate in frequently changing interference conditions.However,existing resource allocation methods typically assume complete interference information or are suitable only for static environments,leading to significant performance degradation in the face of external uncertainties and incomplete information.To address these challenges,this paper employs fuzzy set theory to dynamically model the uncertainty of external interference and defuzzify its impact on the available frequency bands during iterative diagnostics.Additionally,a dynamic constrained multi-objective optimization model is developed,and a novel Dynamic Constrained MultiObjective Evolutionary Algorithm based on Transfer Search(TrS-DCMOEA)is proposed.By integrating transfer learning and dynamic adjustment strategies,the algorithm quickly adapts to environmental changes,ensuring communication performance while maintaining the security of UAV swarm communications.Simulation results show that the proposed algorithm achieves superior decision-making and resource allocation efficiency in most time slots,with TrS-DCMOEA particularly excelling in tracking the Pareto front in dynamic environments. 展开更多
关键词 UAV swarm Resource allocation Dynamic constraints Incomplete information Dynamic decision-making Multi-objective optimization
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基于Informer模型的智能洪水预报方法研究 认领 引用 被引量：1
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作者 董付强 万喆 +3 位作者 王丽娟 蔡金华 万俊 罗永钦 《人民长江》 北大核心 2026年第1期53-63,共11页
洪水预报精度和预见期是做好水库洪水预警和调度的关键,在洪水预报中应用人工智能模型可有效提高洪水预报精度。应用K-means聚类分析法对潘口水库流域进行了科学划分,然后采用Informer深度学习模型进行洪水预报,并与传统LSTM模型进行了... 洪水预报精度和预见期是做好水库洪水预警和调度的关键,在洪水预报中应用人工智能模型可有效提高洪水预报精度。应用K-means聚类分析法对潘口水库流域进行了科学划分,然后采用Informer深度学习模型进行洪水预报,并与传统LSTM模型进行了对比研究,最后基于Informer模型设计了4种预报方案分析上游水库对潘口水库洪水预报精度的影响。结果表明:(1) Informer模型的预报性能优于LSTM模型;(2)优化后的Informer模型,训练集和测试集总体纳什系数为0.892,洪水总量误差为6.64%,洪水峰值误差为7.69%,洪量误差及洪峰误差平均值均达到甲级标准;(3)基于Informer模型的2023年和2024年堵河流域潘口水库实际检验预报纳什系数均值为0.878和0.827,洪量误差及洪峰误差合格率均达100%,均满足甲级要求。基于深度学习Informer模型的智能洪水预报不仅可提高洪量和洪峰的预测精度,而且具有较强的实际应用潜力,可为水库洪水预报预警及防灾减灾提供决策依据。 展开更多
关键词 智能洪水预报 深度学习模型 Informer模型 LSTM模型 潘口水库 堵河
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Application research of a hybrid data-and knowledge-driven artificial intelligence scientific computing model in neutron diffusion calculation for nuclear reactors 认领 引用 被引量：1
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作者 Fu-Lin Zeng Xiao-Long Zhang +1 位作者 Peng-Cheng Zhao Zi-Jing Liu 《Nuclear Science and Techniques》 SCIE EI CAS CSCD 2026年第2期223-244,共22页
Amidst the growing global emphasis on nuclear safety,the integrity of nuclear reactor systems has garnered attention in the aftermath of consequential events.Moreover,the rapid development of artificial intelligence t... Amidst the growing global emphasis on nuclear safety,the integrity of nuclear reactor systems has garnered attention in the aftermath of consequential events.Moreover,the rapid development of artificial intelligence technology has provided immense opportunities to enhance the safety and economy of nuclear energy.However,data-driven deep learning techniques often lack interpretability,which hinders their applicability in the nuclear energy sector.To address this problem,this study proposes a hybrid data-driven and knowledge-driven artificial intelligence model based on physics-informed neural networks to accurately compute the neutron flux distribution inside a nuclear reactor core.Innovative techniques,such as regional decomposition,intelligent keff(effective multiplication factor)search,and keffinversion,have been introduced for the calculation.Furthermore,hyperparameters of the model are automatically optimized using a whale optimization algorithm.A series of computational examples are used to validate the proposed model,demonstrating its applicability,generality,and high accuracy in calculating the neutron flux within the nuclear reactor.The model offers a dependable strategy for computing the neutron flux distribution in nuclear reactors for advanced simulation techniques in the future,including reactor digital twinning.This approach is data-light,requires little to no training data,and still delivers remarkably precise output data. 展开更多
关键词 Neutron diffusion equation Physics informed neural network Effective multiplication factor Whale optimization algorithm
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Deep Learning-Enhanced Human Sensing with Channel State Information: A Survey 认领 引用 被引量：1
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作者 Binglei Yue Aili Jiang +3 位作者 Chun Yang Junwei Lei Heng Liu Yin Zhang 《Computers, Materials & Continua》 SCIE EI 2026年第1期1-28,共28页
With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State I... With the growing advancement of wireless communication technologies,WiFi-based human sensing has gained increasing attention as a non-intrusive and device-free solution.Among the available signal types,Channel State Information(CSI)offers fine-grained temporal,frequency,and spatial insights into multipath propagation,making it a crucial data source for human-centric sensing.Recently,the integration of deep learning has significantly improved the robustness and automation of feature extraction from CSI in complex environments.This paper provides a comprehensive review of deep learning-enhanced human sensing based on CSI.We first outline mainstream CSI acquisition tools and their hardware specifications,then provide a detailed discussion of preprocessing methods such as denoising,time–frequency transformation,data segmentation,and augmentation.Subsequently,we categorize deep learning approaches according to sensing tasks—namely detection,localization,and recognition—and highlight representative models across application scenarios.Finally,we examine key challenges including domain generalization,multi-user interference,and limited data availability,and we propose future research directions involving lightweight model deployment,multimodal data fusion,and semantic-level sensing. 展开更多
关键词 Channel State Information(CSI) human sensing human activity recognition deep learning
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Heterogeneity Performance of Cross-border Development Under the Influence of High-speed Rail Flow and Information Flow in Yangtze River Delta Region,China 认领 引用 被引量：1
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作者 DUAN Wei WANG Shaobo +1 位作者 ZHOU Yutao WANG Xinyu 《Chinese Geographical Science》 SCIE CAS CSCD 2026年第3期524-540,共17页
In the knowledge economy era,the rapid flow channels represented by high-speed rail(HSR)and online information flow promote cross-border development between cities.This study constructed a conceptual model of cross-bo... In the knowledge economy era,the rapid flow channels represented by high-speed rail(HSR)and online information flow promote cross-border development between cities.This study constructed a conceptual model of cross-border development from the perspective of flow space.Taking the Yangtze River Delta Region(YRDR),China,as a case study,we apply the Speaker-listener Label Propagation Algorithm(SLPA)to detect the heterogeneity patterns of cross-border development shaped by HSR flow and information flow in 2021.Results show that cross-border development among cities is more evident under information flows compared to HSR flow.Furthermore,intra-provincial cross-border development predominates under HSR flow,whereas inter-provincial cross-border development is more frequent under in-formation flow.Additionally,information flow leads to more shared or competitive nodes in cross-border development across different communities.In the future,leveraging these nodes'intermediary role will be the key to driving the next phase of regional integration.This research will enhance and broaden the theoretical frameworks for cross-border integrated development,flow space,and regional coordinated development. 展开更多
关键词 flow space cross-border development high-speed rail(HSR)flow information flow Yangtze River Delta Region(YRDR),China
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Hybrid algorithm of quantum gate/annealing and classical computer for truss topology optimization 认领 引用 被引量：1
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作者 Zhenghuan Wang Xiaojun Wang 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第6期76-93,共18页
This paper presents a novel approach for truss topology optimization using a hybrid architecture that integrates gate-based quantum computers,quantum annealers,and classical computing platforms.By leveraging the paral... This paper presents a novel approach for truss topology optimization using a hybrid architecture that integrates gate-based quantum computers,quantum annealers,and classical computing platforms.By leveraging the parallelism and quantum superposition inherent in quantum computers,the proposed method significantly enhances optimization performance,yielding faster results and improved mechanical properties compared to classical methods.Additionally,quantum tunneling mechanisms are employed to efficiently conduct static analysis.The effectiveness of the proposed method is validated through three numerical examples,demonstrating its ability to handle truss topology optimization problems.This hybrid system offers a promising solution for intricate truss optimization tasks,highlighting the potential of quantum computing to advance engineering design and solve real-world challenges more efficiently. 展开更多
关键词 Quantum computing Quantum annealing Topology optimization Quantum information
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基于BIM表达的Laplace变换求解桩土地基动力相互作用 认领 引用 被引量：1
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作者 熊辉 赵铭 《铁道科学与工程学报》 EI CAS CSCD 北大核心 2026年第4期1675-1688,共14页
为高效研究分析群桩-土动力相互作用,结合数值计算和三维可视化,本文基于Laplace变换与建筑信息模型(BIM)技术的深度融合,构建了桩土地基动力相互作用数值计算-三维可视化协同分析框架。基于连续介质动力学理论,建立桩-土黏弹性耦合效... 为高效研究分析群桩-土动力相互作用,结合数值计算和三维可视化,本文基于Laplace变换与建筑信息模型(BIM)技术的深度融合,构建了桩土地基动力相互作用数值计算-三维可视化协同分析框架。基于连续介质动力学理论,建立桩-土黏弹性耦合效应的运动微分方程体系;通过引入Laplace变换,将时域微分方程转换为频域代数方程,有效规避了时域积分步长限制导致的累积误差问题,推导了考虑土体分层特性与桩端约束条件的位移解析解,采用Revit平台开发参数化建模插件,建立包含土层弹阻、群桩体空间、几何参数及材料属性等的频域三维信息模型。通过C#编程语言二次开发,实现了与Revit模型的数据交互,将求得的桩身位移场转化为NURBS曲线控制点坐标,利用SweptBlend方法生成了具有物理真实性的桩体振型曲面,并通过对具体工程实例的应用研究,验证了该方法的可行性。研究结果表明:该方法不仅能够描述群桩在不同工况下的振动特性,还利用BIM的可视化表达结合Laplace变换,使复杂的振型信息更易于理解,并显著提升了群桩-土相互作用分析的效率和精度。研究结果可为桩土地基动力相互作用分析提供具有前瞻性的数字化、可视化与智能化可行方案,并有助于更准确地进行安全评估和降低工程风险。 展开更多
关键词 桩承结构 群桩-土动力反应 群桩阻抗 Laplace变换 BIM(building information model)
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Employee Stock Ownership Plans and Stock-price Informativeness 认领 引用 被引量：2
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作者 Yuehua Zuo Xin Huang +1 位作者 Xiaojun Liu Yunhao Dai 《China & World Economy》 2024年第3期162-190,共29页
This study examines the impact of employee stock ownership plans(ESOPs)on stock-price informativeness in Chinese stock markets.Its findings indicate that firms implementing ESOPs experienced an average 11.89 percent i... This study examines the impact of employee stock ownership plans(ESOPs)on stock-price informativeness in Chinese stock markets.Its findings indicate that firms implementing ESOPs experienced an average 11.89 percent increase in stock-price informativeness.The plans improved stock-price informativeness through increased external attention and supervision.An event study shows that ESOPs gave rise to an announcement effect,driven by anticipated performance improvements and the novelty associated with ESOPs.A mechanism analysis demonstrates that the implementation of ESOPs attracted market attention,and the increased market supervision resulting from this mitigated the moral hazards of management associated with ESOPs.Plans with more positive signals exerted a greater influence.Notably,ESOPs that prioritized management incentives gained more recognition in the market.As the incentive effects of ESOPs were weaker than those of equity incentive plans and the ESOPs lost novelty over time,the annual announcement effect diminished gradually.These findings underscore the necessity of strengthening ESOP incentives for continued optimization of priceefficiency. 展开更多
关键词 announcement effect corporate governance employee stock ownership plan stock-price informativeness
Unlocking Interfacial Charge at Dielectric Solid-Liquid Interfaces via Triboelectric Nanogenerator Probe 认领 引用 被引量：2
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作者 Xiang Li Gehan Amaratunga +1 位作者 Zhong Lin Wang Di Wei 《SmartSys》 2026年第1期4-9,共6页
1|Introduction Electrical double layers(EDLs)are fundamental to solid-liquid interfacial phenomena,orchestrating charge compensation,ionic ordering,and solvent reorganization.Through these coupled processes,EDLs regul... 1|Introduction Electrical double layers(EDLs)are fundamental to solid-liquid interfacial phenomena,orchestrating charge compensation,ionic ordering,and solvent reorganization.Through these coupled processes,EDLs regulate a wide spectrum of behaviors from electrochemical reactivity and colloidal stability to energy transduction and information signaling[1-5].Despite their central importance across chemistry,materials science,and physics,experimental insight into EDLs has been largely shaped by a narrow subset of interfaces,those involving electrically conductive solids[6-9].Classical EDL models,originating from the Helmholtz[10]. 展开更多
关键词 colloidal stability energy transduction electrochemical reactivity triboelectric nanogenerator solid liquid interfaces information signaling despite solvent reorganizationthrough electrical double layers
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Pediatric clinical trials in emergency or intensive care settings using exception from informed consent and waiver of informed consent regulations 认领 引用
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作者 Lili Yang Yayun Wang +2 位作者 Panzhi Wang Siyun Xu Rongwang Yang 《World Journal of Emergency Medicine》 SCIE CAS CSCD 2026年第3期262-264,共3页
Clinical trials in emergency settings are challenging and account for only about 1%of all clinical trials.[1]Approximately 50%of randomized controlled trials(RCTs)in emergency and critical care settings fail to recrui... Clinical trials in emergency settings are challenging and account for only about 1%of all clinical trials.[1]Approximately 50%of randomized controlled trials(RCTs)in emergency and critical care settings fail to recruit patients to time and target.[2]Children are not just small adults.Conducting trials in pediatrics is more challenging than it is in adults.Pediatric patients in emergency and intensive care settings are the most vulnerable population.Therefore,conducting RCTs in pediatric emergency and intensive care settings is challenging because of the special biological heterogeneity and ethical challenges associated with children. 展开更多
关键词 exception informed consent emergency settings intensive care randomized controlled trials clinical trials clinical trials approximately waiver informed consent pediatric clinical trials
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An uncertainty evaluation for storm surge risk analysis based on information utilization efficiency 认领 引用
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作者 Guilin LIU Siyu DING +3 位作者 Shichun SONG Bokai YANG Pengyu ZHU Liping WANG 《Journal of Oceanology and Limnology》 SCIE CAS CSCD 2026年第2期545-559,共15页
With the development of methods for predicting extreme hydrological elements using probabilistic approaches,several commonly used methods have emerged for analyzing the risk of storm surge disasters,including the Annu... With the development of methods for predicting extreme hydrological elements using probabilistic approaches,several commonly used methods have emerged for analyzing the risk of storm surge disasters,including the Annual Maxima method,the Peak-Over-Threshold method,the Gumbel distribution,and the Weibull distribution.Meanwhile,and emphases have been placed on assessing and comparing the applicability and stability of these various methods.To evaluate the rationality of different methods,we an entropy uncertainty analysis method was introduced based on information utilization efficiency,in which the sample Stochastic uncertainty is measured by the ratio of information entropy before and after sampling,i.e.,the information extraction efficiency of the sampling method.Additionally,the cognitive uncertainty of the research method is assessed by the ratio of mutual information between the model and the sample to the information entropy of the sample,i.e.,the information extraction efficiency of the mathematical model.Furthermore,we incorporated the group probability calculation method,information entropy and mutual information theory to analyze and calculate the entropy uncertainty more accurately.By applying this analysis to the design wave height and the recurrence period projected in the sea area west Guangdong of China,we believed that the most reasonable hazard assessment method shall be based on the over-threshold method combined with the Pareto distribution.Conversely,the assessment method based on the process extreme value method is deemed insufficiently reasonable and requires further research. 展开更多
关键词 uncertainty storm surge information entropy mutual information group probability calculation method
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CWSS-IS:A Technical Framework for Digitalized Wastewater Surveillance–Information System Structure,Data Standards,and Application—China,February 2024–January 2026 认领 引用
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作者 Shuxin Hao Liang Zhang +11 位作者 Fuchang Deng Jiayi Han Xia Li Huihui Sun Xiao Zhang Song Tang Lan Zhang Yang Yang Qing Guo Lin Wang Yue Liu Xiaoyuan Yao 《China CDC weekly》 SCIE CSCD 2026年第23期724-729,共6页
Many countries have integrated wastewater monitoring systems with their infectious disease surveillance systems to enhance public health response capabilities.An Information System for the Chinese Urban Wastewater Sur... Many countries have integrated wastewater monitoring systems with their infectious disease surveillance systems to enhance public health response capabilities.An Information System for the Chinese Urban Wastewater Surveillance System(CWSS-IS)was developed based on the unified digital infrastructure of the China CDC.The primary functional modules of the CWSS-IS include information on monitoring sites,wastewater sample collection,relevant physicochemical indicators,qualitative and quantitative laboratory results,and sequencing data.The system implements unified data collection indicators and formats and standardizes data processing procedures and quality control(QC)rules.Launched nationally in February 2024,the CWSS-IS covers 169 cities with>3,000 registered users from CDCs,tracking multiple biomarkers in wastewater treatment plants,hospitals,communities,markets,and inbound flights.By January 2026,data had been collected from 118,729 samples.Compared to previous email-based reporting methods,the CWSS-IS demonstrated significant advantages in terms of efficiency,convenience,security,and scalability.This system offers valuable insights into the prevalence of infectious diseases and can effectively inform public health initiatives.Additionally,it serves as a standard paradigm for developing regional wastewater monitoring information systems.Future efforts should focus on exploring multisource data fusion standards,artificial intelligence frameworks,and large-scale data computational platforms to enhance early warning capabilities. 展开更多
关键词 information system data standards wastewater surveillance digitalized wastewater surveillance integrated wastewater monitoring systems infectious disease surveillance systems unified digital infrastructure information system structure
Author correction:Unsupervised learning enabled label-free singlepixel imaging for resilient information transmission through unknown dynamic scattering media 认领 引用
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作者 Fujie Li Haoyu Zhang +7 位作者 Zhilan Lu Li Yao Yuan Wei Ziwei Li Feng Bao Junwen Zhang Yingjun Zhou Nan Chi 《Opto-Electronic Advances》 SCIE EI CAS CSCD 2026年第2期1-1,共1页
Correction to:Opto-Electronic Advances http://gffzzd3cc09b8251d45dfsfc9fw9pn9pkn6cwu.ffgz.tsg.suse.edu.cn/10.29026/oea.2025.250013 published 25 October 2025 After the publication of this article,it was brought to our attention that the funding information in the Ackno... Correction to:Opto-Electronic Advances http://gffzzd3cc09b8251d45dfsfc9fw9pn9pkn6cwu.ffgz.tsg.suse.edu.cn/10.29026/oea.2025.250013 published 25 October 2025 After the publication of this article,it was brought to our attention that the funding information in the Acknowledgements section contained an error.Correction details are listed below. 展开更多
关键词 single pixel imaging opto electronic advances resilient information transmission label free imaging unknown dynamic scattering media funding information unsupervised learning
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基于TCN-Informer的长短期多变量时间序列预测 认领 引用 被引量：1
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作者 李德权 江涛 《科学技术与工程》 EI 北大核心 2026年第4期1549-1557,共9页
为了解决时间序列预测长期和短期依赖关系的难题,同时捕捉长期趋势和短期动态,并对多变量时间序列中变量间复杂的相互依赖关系进行建模,提出了一种基于时间卷积网络(temporal convolutional network,TCN)的预测方法。首先,采用TCN来有... 为了解决时间序列预测长期和短期依赖关系的难题,同时捕捉长期趋势和短期动态,并对多变量时间序列中变量间复杂的相互依赖关系进行建模,提出了一种基于时间卷积网络(temporal convolutional network,TCN)的预测方法。首先,采用TCN来有效捕捉序列变量在时间尺度上的特征,同时将压缩-激励模块(squeeze-and-excitation block,SE_Block)应用于TCN的输出。该模块通过增强多变量的表示,有效解决短期依赖性问题,并提高模型捕捉关键短期信息的能力。其次,引入Informer模型来增强长期序列处理能力,不仅有效解决了长期序列预测中的计算效率问题,还增强了模型对全局时间依赖关系的建模能力。最后,在设备状态监测(ETTm1)、交通流量(Traffic)和电力负荷(Electricity)三个数据集上将所提方法与现有的时间序列模型进行实验验证并比较。结果表明:所提出的方法在长期和短期时间序列预测中的误差率较低,能够有效提高多变量时间序列中长期和短期预测性能。 展开更多
关键词 长短期时间序列 多变量时间序列 Informer 时间卷积网络(TCN) 特征提取
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Multi-Source Traffic Information Completion and Perception Method via Graph Convolutional Neural Networks in Intelligent Connected Transportation System 认领 引用
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作者 Pangwei Wang Jie Wang +2 位作者 Zipeng Wang Hangrui Dong Li Wang 《Computers, Materials & Continua》 SCIE EI 2026年第8期1417-1435,共19页
Traffic holographic perception refers to the real-time,high-fidelity,and multi-dimensional sensing of traffic states through the fusion of heterogeneous sensors,including cameras,radars,and connected vehicle data.The ... Traffic holographic perception refers to the real-time,high-fidelity,and multi-dimensional sensing of traffic states through the fusion of heterogeneous sensors,including cameras,radars,and connected vehicle data.The multi-source perception data obtained thereby can provide a complete digital representation of the road network for the Intelligent Transportation System(ITS).However,sensors are vulnerable to environmental interference,which can result in data loss at specific points or along arterial highways for certain periods,potentially undermining system safety and decision-making reliability.To address these challenges,a deep learning method based on Graph Convolutional Networks(GCN)and Gated Recurrent Units(GRU)is proposed,leveraging Artificial Intelligence(AI)and intelligent connected technologies for real-time acquisition of multi-sensor perception data.A feature-level fusion integrates multi-source perception data.GCN captures spatial dependencies from the road network topology,while GRU extracts temporal features from time series,enabling accurate imputation of missing traffic data.The method is evaluated at intelligent connected intersections in the Beijing High-level Autonomous Driving Demonstration Area.Results show that the accuracy of long-term traffic state completion reaches 89.36%,and the Root Mean Square Error(RMSE)is reduced by 17.2%compared to the Long Short-Term Memory(LSTM)baseline.This framework provides a practical solution for deploying traffic holographic perception technology in secure and trustworthy ITS. 展开更多
关键词 Intelligent transportation information security traffic information completion traffic holographic perception AI-driven edge computing graph convolutional neural network
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同轴气化通道煤炭地下气化产品气热值分析及预测 认领 引用
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作者 苏发强 李郊源 +5 位作者 李雯 陈艳鹏 刘亚洲 廉松傲 余伊河 周泽 《煤炭学报》 EI CAS CSCD 北大核心 2026年第2期1682-1697,共16页
在煤炭地下气化(UCG)过程中,操作参数和煤的性质不同会导致UCG系统表现出不同的气化过程,产品气热值稳定产出一定时间后也会出现下降趋势。在人工煤层构建2种同轴煤炭地下气化模型,研究同轴气化通道对生成气化产物中气体成分及热值的影... 在煤炭地下气化(UCG)过程中,操作参数和煤的性质不同会导致UCG系统表现出不同的气化过程,产品气热值稳定产出一定时间后也会出现下降趋势。在人工煤层构建2种同轴煤炭地下气化模型,研究同轴气化通道对生成气化产物中气体成分及热值的影响,并对比分析压力、气化剂流量、气体组分对热值的影响,提出Informer热值预测模型,使用ERMS、EMA和R2作为评价指标,将结果与4种机器学习模型(LSTM、MLP、RNN和ARIMA)进行比较,对比分析不同预测时间长度下产品气热值的实际值、预测值及误差。结果表明:不同的同轴气化通道能够影响气化效果,改变气化通道延展长度,可以改变产出气体中可燃气体组分比例。同轴模型1产品气中有效气体组分(CO、H2和CH4)的体积分数为33.45%,平均热值为4.68 MJ/Nm3;同轴模型2产品气中有效气体组分的体积分数为35.09%,平均热值为4.75 MJ/Nm3。相比同轴模型1,在同轴模型2中,H2的体积分数由6.17%提高至8.10%,而CH4的体积分数则由1.19%减少至0.61%。调整气化剂流量会改变气化炉的平衡状态,从而短暂提高产品气热值。与其他参考模型相比,EMA下降了22.42%~42.78%,ERMS下降了15.38%~30.49%,Informer热值预测模型表现优异,预测精度高。模型在不同的数据集、预测长度和采样频率下均具有较高的预测精度。同轴模型1数据集的平均误差为8%~18%,同轴模型2数据集的平均误差为5%~12%。Informer模型在预测不同时间段热值曲线时,能够有效预测出热值变化的不同趋势,且可以预测参数调整后的系统表现。 展开更多
关键词 煤炭地下气化 同轴模型 气化剂流量 Informer模型 热值预测
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Information Security with Smart Hydrogels: Photo-Patterning and Multi-Stimuli Responsive Structural Color 认领 引用
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作者 Xiaoyu Guo Ying Li +5 位作者 Farzana Hanif Linhai Zhu Miao Kong Shufen Zhang Yuang Zhang Bingtao Tang 《Nano-Micro Letters》 SCIE EI CAS CSCD 2026年第9期420-434,共15页
Photonically structured colors, characterized by high resolution and dynamic responsiveness, hold promising prospects in the field of information security. However, conventional patterning methods are often limited by... Photonically structured colors, characterized by high resolution and dynamic responsiveness, hold promising prospects in the field of information security. However, conventional patterning methods are often limited by high equipment costs and monotonous color outputs, which restrict their widespread adoption. To address these issues, this paper proposes a novel multi-color patterning method based on light-induced chemical crosslinking. By introducing light-initiated crosslinking molecules into anti-opal hydrogels, we developed a film that can be further regulated by photo-curing, enabling a “film formation first, then patterning” approach. The structural color hydrogels created using this method can display multi-color patterns, with a minimum line width of 15 μm, significantly enhancing their information-carrying capacity. Moreover, ultraviolet radiation can increase the degree of cross-linking, thereby inhibiting swelling behavior, enhancing tensile strength, reducing elongation at break, and causing the color of the inverse opal structure to shift toward blue or disappear. With inherent responsiveness to stress, temperature, and solvents, this approach enables dynamic information display and has excellent stability(able to cycle stably for more than 100 times). This work introduces a new method for patterning stimulus-responsive structural colors and opens up new possibilities for their use in applications such as ink-free printing, information encryption, and anti-counterfeiting. 展开更多
关键词 Structural color Anti-opal hydrogel Light-induced crosslinking Information security
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