Domain knowledge-driven decomposition-based large-scale optimization for ship cabin structures by Puyu JIANG, Jun LIU, Qiangjun LUO, Yuansheng CHENG

“…ObjectivesThis paper proposes a domain knowledge-driven large-scale optimization algorithm for ship cabin structures based on a decomposition optimization framework. MethodsThe proposed algorithm combines domain mechanical knowledge with a general black box optimization algorithm, groups the design variables into location variables and size variables, and decomposes the original problem into a series of low-dimensional subproblems. …”
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Systematic Literature Review for Robust Mixed-Integer Linear Programming Models Using Benders Decomposition in Facility Location Problems by Fadiah Hasna Nadiatul Haq, Diah Chaerani, Anita Triska

“…The robust Mixed-Integer Linear Programming (MILP) model is an approach to address uncertainty in linear optimization involving integer and continuous variables, which can be solved using the Benders Decomposition method. …”
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Photovoltaic solar energy prediction using the seasonal-trend decomposition layer and ASOA optimized LSTM neural network model by Venkatachalam Mohanasundaram, Balamurugan Rangaswamy

“…Parameter standardization employing ASOA, the RSTL decomposition approach, and the conceptual model of LSTM networks are all presented in this research work. …”
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BUILDING OF MATHEMATICAL MODEL FOR OPTIMIZATION OF COMPOSITIONS OF EFFECTIVE EXOTHERMIC BLENDS by D. M. Kukuj, Ju. N. Fasevich

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Robust Variable Selection via Bayesian LASSO-Composite Quantile Regression with Empirical Likelihood: A Hybrid Sampling Approach by Ruisi Nan, Jingwei Wang, Hanfang Li, Youxi Luo

“…To address this critical limitation, we propose a novel empirical likelihood (EL)-based variable selection framework that integrates a Bayesian LASSO penalty within the composite quantile regression framework. …”
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The Application of Near-Infrared Spectroscopy Combined with Chemometrics in the Determination of the Nutrient Composition in Chinese <i>Cyperus esculentus</i> L. by Xiaobo Jiao, Dongliang Guo, Xinjun Zhang, Yunpeng Su, Rong Ma, Lewen Chen, Kun Tian, Jingyu Su, Tangnuer Sahati, Xiahenazi Aierkenjiang, Jingjing Xia, Liqiong Xie

“…Partial least squares regression (PLSR) was utilized to establish prediction models between NIR and chemical indicators. In addition, to further enhance the prediction performance of the models, various preprocessing and variable selection algorithms were utilized to optimize the prediction models. …”
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Application Of The Denitrification-Decomposition (DNDC) Model To Retrospective Analysis Of The Carbon Cycle Components In Agrolandscapes Of The Central Forest Zone Of European Russ... by Olga E. Sukhoveeva, Dmitry V. Karelin

“…We applied the process-based simulation model DNDC (DeNitrification-DeComposition) recommended  by UNCCC and world widely used.  …”
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Investigation and optimization of battery thermal management system based on composite phase change material and variable wall liquid cooling plate by Xiaoyong Gu, Wenbo Lei, Jiacheng Xi, Mengqiang Song

“…To mitigate the risk of thermal runaway in lithium-ion batteries, an efficient battery thermal management system (BTMS) assumes paramount importance. A BTMS based on composite phase change material (CPCM) and variable wall liquid cooling plate (LCP) is proposed in this research. …”
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The Optimization Design of Variable Valve Parameters for Internal Combustion Engines Considering the Energy Consumption of a Composite Electromagnetic Valve Mechanism by Xinyu Fan, Juyi Han, Jie Yin, Li Zheng, Wei Shao

“…To this end, this paper establishes a thermodynamic model of the engine based on the composite electromagnetic valve mechanism. …”
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Analysis of the Impact of Global Oil Prices On GDP (on the Example of the Azerbaijan Republic) by N. S. Ayyubova

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The Impact of Malted Grains on Human Intestinal Microbiota Composition in an In Vitro Model by Carlos Gómez-Gallego, Roosa-Maria Willman, Kati Martikainen, Marjukka Kolehmainen

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Analysis of effects of meteorological variables on dengue incidence in Bangladesh using VAR and Granger causality approach by Md. Jamal Hossain, Nazia Sultana, Anwesha Das, Fariea Nazim Jui, Md. Kamrul Islam, Md. Mijanoor Rahman, Mohammad Mafizur Rahman

“…While previous studies have examined the relationship between dengue and meteorological variables using single model approaches, this study employs advanced econometric techniques to capture dynamic interactions. …”
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Compositional and Machine Learning Tools to Model Plant Nutrition: Overview and Perspectives by Léon Etienne Parent

“…The additive and orthogonal log ratios of CoDa reduce a <i>D</i>-parts soil composition to <i>D</i>-1 variables, alleviating redundancy in the predictive ML models. …”
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Penalized Composite Likelihood Estimation for Spatial Generalized Linear Mixed Models by Mohsen Mohammadzadeh, Leyla Salehi

“…When discussing non-Gaussian spatially correlated variables, generalized linear mixed models have enough flexibility for modeling various data types. …”
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Resampling Multi-Resolution Signals Using the Bag of Functions Framework: Addressing Variable Sampling Rates in Time Series Data by David Orlando Salazar Torres, Diyar Altinses, Andreas Schwung

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Influence of microstructure on rate-dependent response of unidirectional fibrous composites by Soňa Valentová, Michal Šejnoha, Jan Vorel, Zdeněk Prošek

“…The viscoelastic response of the matrix phase was represented by the Maxwell chain model. A series of creep tests performed at several stress levels served as a stepping stone for the model calibration. …”
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EXCHANGE RATE DYNAMICS AND FORECASTING ACCURACY IN EMERGINGECONOMIES: INTEGRATING ENSEMBLE LEARNING MODELS WITH STRUCTURAL TIME SERIES DECOMPOSITION FOR THE USD/ZAR RATE by Agbeyinka Yinka Ibrahim

“…The study offers relevant policy insights for monetary authorities and financial market participants, and recommends the integration of hybrid modeling frameworks that combine machine learning with structural macroeconomic variables. …”
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Spatiotemporal Analysis and Anomalous Trends of Asia AOD (2001–2024): Insights from a Deep Learning Fusion Model and EOF Decomposition by Yu Ding, Wenjia Ni, Jiaxin Dong, Jie Yang, Shiyao Meng, Siwei Li

“…To overcome these challenges, this study employs the deep learning model TabNet, incorporating Digital Elevation Model (DEM) data and ERA5 meteorological variables, to fuse MERRA-2 AOD with MODIS MAIAC AOD observations. …”
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Monitoring and modelling of variables affecting isomerate octane number produced from an industrial isomerization process by Walaa Mahmoud Shehata, Mohamed Fathy Mohamed, Fatma Khalifa Gad

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The uncertainty of estimation of doses to the bone marrow from ^89,90Sr due to the variability of the chemical composition and bone density by E. A. Shishkina, P. A. Sharagin, E. A. Tolstykh

“…The objective of this study is to assess the influence of variability of chemical composition and bone density on the results of dosimetric modeling. …”
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