Assessing the global burden of interstitial lung disease and pulmonary sarcoidosis using multiple statistical models: analysis and future projections by Luna Zhao, Yue Zhou, Yun Jia, Lang Wang, Ye Liu, Guizhen Lv, Yihao Zhang, Jinyang Li, Junfeng Ren, Hongzheng Liu, Yufeng Zhang, Ning Wang, Wenwen Zhang, Wenqiang Mo, Jiaqi Liu, Yilin Wang, Junhao Ma, Chao Wu, Dong Liu, GBD Collaborator

“…Temporal trends were evaluated using average annual percentage change (AAPC), age-period-cohort (APC), and Bayesian APC (BAPC) models. Decomposition analysis and Pearson’s correlation analysis were conducted to assess the impact of aging, population growth, and sociodemographic index (SDI). …”
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RESEARCH OF DIKW AND 5C ARCHITECTURAL MODELS FOR CREATION OF CYBER-PHYSICAL PRODUCTION SYSTEMS WITHIN THE CONCEPT OF INDUSTRY 4.0 by Sergei Osadchy, Nataliia Demska, Yuriy Oleksandrov, Viktoriia Nevliudova

“…The research carried out is based on the methods of decomposition and formalized representation of systems. …”
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Deep VMD-attention network for arrhythmia signal classification based on Hodgkin-Huxley model and multi-objective crayfish optimization algorithm. by Hang Zhao, Xiongfei Yin

“…The ablation study evaluated the effectiveness of the proposed signal decomposition method and deep attention modules. The model based on MOCOA-VMD achieves the highest accuracy of 94.46%, outperforming models constructed using EEMD, VMD, CNN and LSTM modules. …”
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Anisotropic error estimator for the Stokes–Biot system by Houédanou Koffi Wilfrid

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Attention-Based CNN Fusion Model for Emotion Recognition During Walking Using Discrete Wavelet Transform on EEG and Inertial Signals by Yan Zhao, Ming Guo, Xiangyong Chen, Jianqiang Sun, Jianlong Qiu

“…An investigation is made on the effect of diverse mother wavelet types and wavelet decomposition levels on model performance which indicates that the 2.2-order reverse biorthogonal (rbio2.2) wavelet with two-level decomposition has the best recognition performance. …”
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Assessment of Large‐Scale Reservoirs' Impact on the Local Precipitation by Han Zhou, Jun Qiu, Mengjia Li, Houliang Lu, Fangfang Li

“…Instead of assuming that the natural variability of the contrast region and the study region is identical, this study develops an interpretable machine learning model to investigate relationships between precipitation‐influencing factors and precipitation itself, including both stable components (sum of trend and seasonality from STL decomposition) and random components (residuals after removing trend and seasonality), which is then used to forecast natural precipitation in the absence of reservoir operation. …”
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Disentangled diffusion dodels for probabilistic spatio-temporal traffic forecasting by Wenyu Zhang, Kaidong Zheng

“…These methods typically rely on deterministic models, which struggle to capture and represent the random fluctuations and sudden changes within traffic data, limiting the reliability and accuracy of their predictions. …”
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Crop Model Ensemble Averaging: A Large But Underappreciated Uncertainty Source for Global Crop Yield Projections Under Climate Change by Xiaomeng Yin, Guoyong Leng, Jiali Qiu, Xiaoyong Liao, Shengzhi Huang, Jian Peng

“…Regionally, the largest uncertainties from the choice of ensemble averaging methods are observed in Indonesia and Canada. Further uncertainty decomposition analysis shows that ensemble averaging methods contributes to 39%–87% of total uncertainties for global yield projections, which is even higher than climate models. …”
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Financial Dynamics of Cooperatives of the Popular and Solidarity Economy of Ecuador: An Analysis Using the Tucker3 Model and Projection with Multidimensional Neutrosophic Regressio... by Gabriela Valeria Bustos–Chiliquinga, Purificación Galindo-Villardón, Cristian Cornejo Gaete

“…This study relies on the Tucker3 model as a factorization model of multivariate analyses since the goal is to evaluate the financial dependency structure of Ecuador's cooperative sector of the Popular and Solidarity Economy (PSE) between 2016–2023. …”
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Inequality in opportunities for utilizing community-based care services among the elderly in China – an analysis based on the “circumstance-effort” perspective by He Jiang, Yanshuo Huang

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A frequentist one-step model for a simple network meta-analysis of time-to-event data in presence of an effect modifier. by Matthieu Faron, Pierre Blanchard, Laureen Ribassin-Majed, Jean-Pierre Pignon, Stefan Michiels, Gwénaël Le Teuff

“…<h4>Methods</h4>One-step, frequentist, IPD-based Cox and Poisson generalized linear mixed models were proposed. …”
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Comparing the trends of cancer burden attributed to high BMI in China and globally from 1990 to 2021, with multi-model prediction to 2036 by Nanting Chen, Nanting Chen, Lingzhi Xing, Lingzhi Xing, Fengyun Xiang, Fengyun Xiang, Chengmiao Li, Chengmiao Li, Letai Li, Jingsong Cheng, Yangfan Yu, Yubowen Gong, Xiao Liu, Fangjiao Xie, Ling Chen

“…Decomposition and age-period-cohort analyses were conducted to identify influential factors, while future trends were projected with the Bayesian age-period-cohort (BAPC), auto-regressive moving average model (ARIMA), and exponential smoothing model (ETS).ResultsIn China, the age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life-years rate (ASDR) for high BMI-attributed cancer increased to 2.81 (95% UI: 1.20–4.76)/105 and 79.17 (95% UI: 33.82–134.14)/105 in 2021, remaining below the global average. …”
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UniLF: A novel short-term load forecasting model uniformly considering various features from multivariate load data by Shiyang Zhou, Qingyong Zhang, Peng Xiao, Bingrong Xu, Geshuai Luo

“…To address the above problems, we design a novel STLF model called UniLF based on Transformer framework, which contains the proposed convolutional enhancement-fusion embedding method to capture the correlations between load and covariates for embedding, the proposed feature reconstruction-decomposition block to distill multiscale features as well as more detailed local-global variations from 2D space and the core mask-guided multiscale interactive self-attention mechanism to further realize the enhanced interactions of scale features and temporal features. …”
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Evaluation of food waste treatment techniques using aczel alsina based MAGDM model in the q-rung orthopair fuzzy soft structure by Rana Muhammad Zulqarnain, Hongwei Wang, Usman Zulfiqar, Rifaqat Ali, Imran Siddique, Abdullatif Saleh Ghallab, Hafiz Shahzar Riaz Khan Tareen, Sohaib Abdal

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Optimal level and order of the Coiflets wavelet in the VAR time series denoise analysis by Intisar Ibrahim Elias, Taha Hussein Ali

“…Through the research results, the efficiency of the proposed method was reached in estimating the parameters of the VAR time series model, effectively treating noise, and determining the optimal Coiflets level and order.…”
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Research on fault diagnosis of amorphous alloy transformers by using vibration signals and a PSO-optimized full-process WPT-SVM model by Daosheng Liu, Wentao Yang, Longsheng Liu, Zhe Zhao

“…The prominent vibration characteristics of amorphous alloy transformer (AMT) make it possible to apply the vibration method for real-time fault monitoring of AMT. Therefore, in order to solve the AMT vibration monitoring problem and enhance the diagnostic efficiency, this study proposes an AMT fault diagnosis model based on particle swarm optimization (PSO) to optimize the parameters of wavelet packet transform (WPT) and support vector machine (SVM).The optimal vibration signal acquisition point is determined by finite element analysis to ensure high signal quality. …”
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A machine learning-based predictive model for the occurrence of lower extremity deep vein thrombosis after laparoscopic surgery in abdominal surgery by Su-Zhen Yang, Ming-Hui Peng, Quan Lin, Shi-Wei Guan, Kai-Lun Zhang, Hai-Bo Yu

“…We employed two interpretability methods: decomposition interpretation and Shapley additive explanation. …”
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SIMULATION OF NITROGEN BALANCE UNDER SUB-SURFACE DRAINAGE CONDITIONS AT THEHRI MUKTSAR PUNJAB, USING THE DNDC MODEL V. 9.5 by MEHRAJ U DIN DAR, J. P. Singh, Kuldip Singh

“…Material and methods: The DeNitrification-DeComposition (DNDC) model is a computer simulation model for the biogeochemistry of carbon and nitrogen in agro ecosystems that takes a process-oriented approach. …”
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A Fusion Modeling Approach for Six-Phase Hybrid Excitation Synchronous Motor, Leveraging Finite-Element Analysis, and Experimental Data-Driven by Xiao Zeng, Yunhao Ma, Jiali Wan, Yiyu Liu

“…The first one is carried out by vector space decomposition method with consideration of delta connection in stator windings. …”
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A Novel BiGRU-Attention Model for Predicting Corn Market Prices Based on Multi-Feature Fusion and Grey Wolf Optimization by Yang Feng, Xiaonan Hu, Songsong Hou, Yan Guo

“…Therefore, this paper proposes a comprehensive, efficient, and accurate method for predicting corn prices. First, in the data processing phase, the seasonal and trend decomposition using LOESS (STL) algorithm was used to extract the trend, seasonality, and residual components of corn prices, combined with the GARCH-in-mean (GARCH-M) model to delve into the volatility clustering characteristics. …”
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