A Topology Identification Framework for Medium and Low Voltage Distribution Networks Driven by Multiple Source Data by Chaoyang ZHU, Dongsheng JING, Heting LI, Yibin WANG, Ping HE

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Research on distributed data spatial architecture model for ownership governance by SUN Jinye, GUO Shuxing

“…Subsequently, a distributed data space architecture model based on the perspective of cross-domain collaboration for data authorization operators was innovatively proposed by combining distributed architecture theory with dynamic It is found that the architecture model can effectively guide the application of cross-domain scenarios so that different dimensions' data can generate large-scale gain value through superposition and optimize ownership allocation to improve orderliness in data market transactions.…”
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Research on distributed data spatial architecture model for ownership governance by SUN Jinye, GUO Shuxing

“…Subsequently, a distributed data space architecture model based on the perspective of cross-domain collaboration for data authorization operators was innovatively proposed by combining distributed architecture theory with dynamic It is found that the architecture model can effectively guide the application of cross-domain scenarios so that different dimensions' data can generate large-scale gain value through superposition and optimize ownership allocation to improve orderliness in data market transactions.…”
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Knowledge-data-driven power flow calculation for lowvoltage active distribution network considering gray data by LIU Siliang, ZHENG Zenan, ZHANG Yongjun, YI Yingqi, CHI Yuquan

“…Inaccurate topology and line parameters in low-voltage distribution networks (LVDNs) render traditional power flow calculation methods ineffective. …”
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Time-division prediction method for peak power of distributed new energy access power grid based on ARIMA–RBF by Yangrui Zhang, Junpeng Zhao, Chao Zhang, Bingyu Zhang, Xiaoyu Liu, Shaokang Feng

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One-shot generative distribution matching for augmented RF-based UAV identification by Amir Kazemi, Salar Basiri, Volodymyr Kindratenko, Srinivasa Salapaka

“…This approach, when utilizing a distributional distance metric, demonstrates significant promise in low-data regimes, outperforming deep generative methods such as conditional generative adversarial networks (GANs) and variational autoencoders (VAEs). …”
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Simulation and Experimental Study of Arc Model in a Low-Voltage Distribution Network by Binbin Zhang, Jiaqing Zhang, Yifeng Cheng, Qixu Chen, Qian Zhang

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A Data-Driven State Estimation Based on Sample Migration for Low-Observable Distribution Networks by Hao Jiao, Chen Wu, Lei Wei, Jinming Chen, Yang Xu, Manyun Huang

“…This paper proposes a data-driven state estimation based on sample migration for low-observable distribution networks, addressing the challenge of traditional state estimators being unsuitable for distribution networks with low observability. …”
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Data-Driven Dynamic Optimization for Hosting Capacity Forecasting in Low-Voltage Grids by Md Tariqul Islam, M. J. Hossain, Md Ahasan Habib

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Modeling Exon-Specific Bias Distribution Improves the Analysis of RNA-Seq Data. by Xuejun Liu, Li Zhang, Songcan Chen

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ADS-B data gating technique and its probabilistic models by E. A. Rubtsov, S. A. Kudryakov, Ia. M. Dalinger, A. S. Kalintsev

“…Probabilistic models of the ADS-B data gating technique, as well as the algorithm for applying these models were proposed. …”
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Real-Time Identification Algorithm of Daylight Space Debris Laser Ranging Data Based on Observation Data Distribution Model by Yang Liu, Xue Dong, Jian Gao, Bowen Guan, Yanning Zheng, Zhipeng Liang, Xingwei Han, He Dong

“…It then employs the goodness-of-fit test of the geometric distribution to ascertain the data distribution law. …”
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Toward a Data‐Effective Calibration of a Fully Distributed Catchment Water Quality Model by Salman Ghaffar, Xiangqian Zhou, Seifeddine Jomaa, Xiaoqiang Yang, Günter Meon, Michael Rode

“…Abstract Distributed hydrological water quality models are increasingly being used to manage natural resources at the catchment scale but there are no calibration guidelines for selecting the most effective gauging stations. …”
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Parameter Estimation for Line Impedance in Distribution Network Based on μPMU Data by Zitong ZHANG, Qun ZHOU, Yulin DIAN, Zichao GUAN, Yue YIN, Minrui LENG, Xueshan LIU

“…In order to solve the long standing issue of missing line impedance parameters in low voltage distribution network, this paper proposed a new approach based on measurement data collected from the micro-synchronous phasor measuring unit (μPMU). …”
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Application of distributed techniques in large language model training and inference by ZHENG Weimin

“…In the data preprocessing stage, an efficient big data processing engine called "Chukonu" was developed to address the issue of high overhead in reading data from distributed file systems. …”
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Estimation of the vertical distribution of the fine canopy fuel in Pinus sylvestris stands using low density LiDAR data by L. A. Fidalgo-González, S. Arellano-Pérez, J. G. Álvarez-González, F. Castedo-Dorado, A. D. Ruiz-González, E. González-Ferreiro

“…The goal of the present study is to model the vertical profile of available canopy fuels in Scots pine stands by using data from the Spanish national forest inventory and low-density LiDAR data (0.5 first returns  m–2) provided by Spanish PNOA project (Plan Nacional de Ortofotografía Aérea). …”
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Low-Voltage Power Restoration Based on Fog Computing Load Forecasting and Data-Driven Wasserstein Distributionally Robust Optimization by Ruoxi Liu, Yifan Song, Yuan Gui, Hanqi Dai, Zhiyong Wang, Chengdong Yin, Qinglei Qin, Wenqin Yang, Yue Wang

“…This paper proposes a fault self-healing recovery strategy for passive low-voltage power station areas (LVPSAs). Firstly, being aware of the typical structure and communication conditions of the LVPSAs, a fog computing load forecasting method is proposed based on a dynamic aggregation of incremental learning models. …”
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Micro and macro particle modelling approach of Co-torrefaction of low-rank coal and biomass by Jenny Rizkiana, Aghietyas Choirun Az Zahra, Salman Alfarisi, Pradhipta Rizka Lakzita, Winny Wulandari, Dwiwahju Sasongko, Guoqing Guan, Francesco Thadeo

“…This study developed a mathematical model for the co-torrefaction of low-rank coal and biomass, aiming to predict the final mass of solid produced and temperature distribution within a particle. …”
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A siamese neural network model for phase identification in distribution networks by Dong Liu, Juan S. Giraldo, Peter Palensky, Pedro P. Vergara

“…Distribution system operators (DSOs) often lack high-quality data on low-voltage distribution networks (LVDNs), including the topology and the phase connection of residential customers. …”
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Assessing uncertainty in forecasts of refugia for Joshua trees using high‐density distribution data by Daniel F. Shryock, Todd C. Esque, Gabrielle A. Berry, Lesley A. DeFalco

“…Predicting Joshua tree responses to impending climate variability, along with the extent of suitable future habitat and/or climate refugia, is critical to ongoing management planning. Previous modeling efforts have been hampered by incomplete distribution data and are now out‐of‐date with the most recent global climate projections. …”
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