A P2P Electricity-Carbon Trading Mechanism for Distributed Prosumers Based on Carbon Emission Flow Model by ZHAN Bochun, FENG Changsen, WANG Xiaohui, ZHANG Heng, MA Junwei, WEN Fushuan

“…Based on the improved Benders decomposition method, the original problem is decomposed into the main problem considering network constraints and the subproblem of optimal scheduling for prosumers. …”
Get full text

Flow Field Prediction of Gas-Solid Fluidized Bed Based on POD and Surrogate Model by Jialei FENG, Xiaohui ZHAO, Nan TU, Jiabin FANG, Ruihe HU, Yibo XU

“…Aiming at the problems of complex two-phase flow and high computational cost in CFD numerical simulation of gas-solid fluidized beds, a reduced-order model for investigating the fluid dynamics in a non-reactive gas-solid fluidized bed was established based on the proper orthogonal decomposition (POD) and the surrogate model. …”
Get full text

Reinforcing Moving Linear Model Approach: Theoretical Assessment of Parameter Estimation and Outlier Detection by Koki Kyo

“…Second, we enhance the extended ML (EML) model by introducing a new outlier detection and estimation method that identifies both the number and locations of outliers by maximizing the reduction in AIC. …”
Get full text

Acoustic Emission Monitoring Method for Multi-Strand Fractures in Post-Tensioned Prestressed Hollow Core Slab Bridges Using Waveguide Rods by Wei Yan, Shiwei Niu, Wei Liu, Juan Li, Shu Si, Xilong Qi, Shengli Li, Nan Jiang, Shuhan Chen, Guangming Wu

Get full text

CEEMDAN-IHO-SVM: A Machine Learning Research Model for Valve Leak Diagnosis by Ruixue Wang, Ning Zhao

“…To address this problem, this paper proposes a feature extraction method based on the combination of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and Fuzzy Entropy (FN). …”
Get full text

Three-stage hybrid modeling for real-time streamflow prediction in data-scarce regions by Awad M. Ali, Mohammed Abdallah, Babak Mohammadi, Hussam Eldin Elzain

“…These findings underscore the importance of signal decomposition for refining data-driven models, facilitating better hydrological prediction and decision-making in data-scarce regions.…”
Get full text

On Holt Winters Algorithm with Decomposition for Forecasting Financial Time Series with Complex Seasonal Patterns by منى نزيه على عبد البارى

Get full text

Multi-Satellite Task Parallelism via Priority-Aware Decomposition and Dynamic Resource Mapping by Shangpeng Wang, Chenyuan Zhang, Zihan Su, Limin Liu, Jun Long

“…To address these problems, this paper proposes a task decomposition and resource mapping method based on task priorities and resource constraints. …”
Get full text

Spectral Quadratic Variation Regularized Autoweighted Tensor Ring Decomposition for Hyperspectral Image Reconstruction by Xinwei Wan, Dan Li, Fanqiang Kong, Yanyan Lv, Qiang Wang

“…The effectiveness of model-based reconstruction methods can be promoted. …”
Get full text

3D Multi-Domain MFS Analysis of Sound Pressure Level Reduction Between Connected Enclosures by Luıs GODINHO, Fernando G. BRANCO, Paulo AMADO MENDES

“…It is important to note that, for such a configuration, a tra- ditional single-domain approach using methods like the MFS or the BEM would lead to undetermined equation systems, and thus the proposed model makes use of a domain decomposition technique.…”
Get full text

Logarithmic Mean Divisia Index Analysis and Dynamic Back Propagation Neural Network Prediction of Transport Carbon Emissions in Henan Province by Changjiang Mao, Jian Luo, Shengyang Jiao, Bin Zhao

“…This study applied the LMDI decomposition method and a BP neural network model to thoroughly analyse the factors influencing carbon emissions in Henan Province’s transportation sector and forecast future trends. …”
Get full text

An experimental analysis method for the incident sound field using propagation mode expansion: Study on the incident sound field in the insulation performance measurement for parti... by Yu Aida, Naohisa Inoue, Tetsuya Sakuma

Get full text

Adaptive Anomaly Detection in Network Flows With Low-Rank Tensor Decompositions and Deep Unrolling by Lukas Schynol, Marius Pesavento

“…We first propose a novel block-successive convex approximation algorithm based on a regularized model-fitting objective where the normal flows are modeled as low-rank tensors and anomalies as sparse. …”
Get full text

Kinetic Analysis of Cement–Asbestos Materials’ Thermal Decomposition Process by an Ex Situ Technique by Robert Kusiorowski, Anna Gerle, Magdalena Kujawa

“…Kinetic analysis of the isothermal data using an Avrami–Erofeev model yielded values for the overall reaction order. …”
Get full text

Block-Based Multicut Benders Decomposition Algorithm for Transmission and Energy Storage Co-Planning by Edimar José de Oliveira, Arthur Neves de Paula, Leonardo Willer de Oliveira, Leonardo de Mello Honório

“…This division makes it possible to use parallel computation methods to solve each block simultaneously, reducing the simulation time, which allows the use of a more extensive time window to model the variability of random variables of the system, such as wind and load. …”
Get full text

A Multi-Scale Unsupervised Feature Extraction Network with Structured Layer-Wise Decomposition by Yusuf Şevki Günaydın, Baha Şen

“…Experimental results on classification and image segmentation tasks show that the proposed method enhances model performance by enriching input representations. …”
Get full text

Range–Null Space Decomposition With Frequency-Oriented Mamba for Spectral Superresolution by Meimei Weng, Jianjun Liu, Jinlong Yang, Zebin Wu, Liang Xiao

“…To address these issues, we propose a model-driven SSR network that integrates range-null space decomposition with deep learning. …”
Get full text

Short-term output prediction of wind-photovoltaic power based on time-frequency decomposition by Yangfan Zhang, Xuejiao Fu, Yaohan Wang, Zhengyu Wang, Xiaoxiao Wang

“…The proposed time-frequency decomposition with the smallest root mean square error of 0.92 and mean absolute error of 0.58 in photovoltaic prediction, at the same time, the smallest root mean square error of 67.5 and mean absolute error of 48.16 in wind power prediction, significantly outperforming other power prediction methods.…”
Get full text

Singular Vectors in Acoustic Simulation Tests of St. Paul the Apostle Church in Bochnia by Krzysztof KOSAŁA

Get full text

Facial recognition targeted attack algorithm based on multiscale frequency decomposition and meta-learning by CAI Jun, HUANG Tianqiang, ZHENG Aokun, YE Feng, XU Chao

“…To address this issue, a facial recognition targeted attack algorithm based on multiscale frequency decomposition and meta-learning was proposed. This algorithm initially devised a multiscale frequency decomposition module that meticulously partitioned the target facial image into frequency bands comprising distinct components. …”
Get full text