A Systematic Literature Review on Flow Data-Based Techniques for Automated Leak Management in Water Distribution Systems by Gopika Rajan, Songnian Li

“…The findings highlight the growing potential of data-driven approaches to enhance leak detection accuracy and efficiency, particularly those leveraging flow and pressure data. …”
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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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Vertical Distribution of Suspended Sediment under Steady Flow: Existing Theories and Fractional Derivative Model by Shiqian Nie, HongGuang Sun, Yong Zhang, Dong Chen, Wen Chen, Li Chen, Sydney Schaefer

“…The fractional advection-diffusion equation (fADE) model is a new approach to describe the vertical distribution of suspended sediment concentration in steady turbulent flow. …”
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Validation and Application of CFD Methodology for Core Inlet Flow Distribution in APR1000 Reactor by Sung Man Son, Won Man Park, Dae Kyung Choi, Choengryul Choi

“…This study addresses these limitations by developing and validating a robust computational fluid dynamics (CFD) methodology to accurately analyze the core inlet flow distribution. A 1/5 scaled-down experimental model adhering to similarity laws was employed for validation. …”
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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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Modeling biogeochemical processes in the Azov Sea using statistically processed data on river flow by A. I. Sukhinov, Y. V. Belova, A. V. Nikitina, A. M. Atayan

“…This explains the need for statistical processing of the data from long-term observations over the river flow characteristics.Materials and Methods. …”
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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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Application of Three-Phase Linearized Power Flow and Line Loss Analysis of Distribution Network Driven by Data and Physics Fusion by Huaitian MU, Hongliang LIAN, Juan LIU, Yanqiong LI

“…In order to solve the above problems, this paper proposed a smoothing model considering on-load tap changer regulation and distributed generation droop control and constructed a fast calculation model of linearized theoretical line loss of a three-phase distribution network driven by data and physics fusion. …”
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Experimental dataset of fluid flow and heat transfer in a shallow packed bed at low Reynolds numbersMendeley Data by Anika Weber, Sebastian Schürg, Timo Roeder, Johannes Grobbel, Martina Neises-von Puttkamer, Christian Sattler

“…The fluid velocity into the packed bed was conditioned to be almost homogeneous, which is achieved by wire screens and checked for in detailed flow pretests.For each of the 9 experiments, the generated data consists of measurements of various temperatures, pressures, ambient conditions and air mass flow, all collected about 60 times per second during the whole experiment, i.e. from the beginning of heating to the end of cooling, which takes up to 300 minutes. …”
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Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data by Yonghua Song, Ge Chen, Hongcai Zhang

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Modeling inter-city population flows: a Deep Radiation model with multisource geographic features by Jingjing Liu, Lei Xu, Le Ma, Chao Wang, Nengcheng Chen

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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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Application of Remote Sensing Floodplain Vegetation Data in a Dynamic Roughness Distributed Runoff Model by Andre A. Fortes, Masakazu Hashimoto, Keiko Udo

“…Studies that consider vegetation in flow modeling rely on unmanned aerial vehicle (UAV) data, which restrict the covered area. …”
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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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A Distributed Machine Learning-Based Scheme for Real-Time Highway Traffic Flow Prediction in Internet of Vehicles by Hani Alnami, Imad Mahgoub, Hamzah Al-Najada, Easa Alalwany

“…Due to the variance of traffic flow patterns between segments, we build a global Distributed Machine Learning Random Forest (DMLRF) regression model to improve the system performance for abnormal traffic flows. …”
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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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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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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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Research on the Modelling and Analysis of the Penetration of Renewable Sources and Storage into Electrical Networks by Eva Simonič, Sebastijan Seme, Klemen Sredenšek

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