Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation by Dan Xu, Yanfeng Li, Anguo Dai, Shumei Zhao, Weitang Song

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Investigating the Capabilities of Ensemble Machine Learning Model in Identifying Near-Fault Pulse-Like Ground Motions by Jafar Al Thawabteh, Jamal Al Adwan, Yazan Alzubi, Ahmad Al-Elwan

“…The study evaluates the effectiveness of these ensemble models in comparison to traditional methods, focusing on their ability to manage the unique attributes of pulse-like ground motions. …”
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Modeling the System of Economic Security of AgroHoldings as the Basis for their Sustainable Development in the Context of Global Crisis Management by A. V. Gluschchenko, E. P. Kucherova, M. V. Denisov

“…The current global fnancial crisis, which is global and systemic, revealed a lack of effective theoretical approaches to the development of practical methods for overcoming the crisis phenomena used in the management of integrated agro-formations. …”
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Wetland Scene Segmentation of Remote Sensing Images Based on Lie Group Feature and Graph Cut Model by Canyu Chen, Guobin Zhu, Xiliang Chen

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High-quality imaging under low scattering conditions using the light field contribution matrix model by Kang Liu, Jia Wu, Jing Cao, Rusheng Zhuo, Xiaoxi Chen, Qiang Zhou, Pinghe Wang, Guohua Shi

“…However, traditional TM construction methods usually require capturing a large number of light field images, a process that is both time-consuming and complex, limiting its widespread use in practical applications. …”
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Development and Validation of a Coupled Hygro-Chemical and Thermal Transport Model in Concrete Using Parallel FEM by Okpin Na, Giyeol Lee

“…The model was numerically implemented using a parallel FE method with the Crank–Nicolson scheme, supported by domain decomposition and SPMD techniques for high computational efficiency. …”
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Theoretical and Numerical Analysis of Soil-Pipe Pile Horizontal Vibration Based on the Fractional Derivative Viscoelastic Model by Hao Zhang, Jienan Niu, Ningning Huang, Qifang Yan

“…The horizontal dynamic control equations of soil layers are derived by using the fractional derivative viscoelastic model. Considering the fractional derivative properties, soil layer boundary condition, and contact condition of pile and soil, the potential function decomposition method is used to solve the radial and circumferential displacements of the soil layer. …”
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DOES ISLAMIC FINANCE DRIVE ECONOMIC GROWTH IN INDONESIA? AN ANALYSIS USING VECTOR ERROR CORRECTION MODEL by Eko Kurniawan, Lina Nugraha Rani, Tanza Dona Pertiwi

“…The analysis is conducted using the vector error correction model (VECM), beginning with stationarity testing, optimal lag selection, cointegration testing, model estimation, and variance decomposition analysis. …”
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ResilioMate: A Resilient Multi-Agent Task Executing Framework for Enhancing Small Language Models by Yubing Xiong, Mingrui Huang, Xuechen Liang, Meiling Tao

“…This research introduces ResilioMate, a resilient multi-agent framework that enhances SLMs by utilizing distributed cognitive burden distribution, dual-scale memory systems, and collaborative bias prevention strategies. The method employs dynamic task decomposition across specialized agents (e.g., Assistant, Checker) to minimize computational costs and combines short-term trajectory tracking with long-term self-reflective optimization for adaptive execution. …”
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Formation of general professional competencies of future teachers in the context of digital transformation of education by Galina A. Ignatieva, Ekaterina Yu. Elizarova

“…., necessitates the creation of a model of such coupling. Purpose – to describe a model of training future teachers at a university, which reflects the process of forming the general professional competencies of future teachers using digital technologies, which determines the content, organizational forms, and methods of their training, contributing to improving the quality of their training. …”
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Comparative analysis of the integration of autologous and allogeneic cryopreserved tendons in the femoral canal on a model of laboratory animals by A. A. Budaev, N. S. Tropskaya, N. V. Borovkova, A. M. Fayn, G. P. Titova, M. S. Makarov, A. Yu. Vaza, I. V. Ponomarev, E. A. Kislyakova, O. S. Kislitsyna, A. A. Offitserov, D. A. Kisel', M. V. Storozheva, V. V. Slastinin, A. A. Kanibolotskiy

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Long-Term Hourly Ozone Forecasting via Time–Frequency Analysis of ICEEMDAN-Decomposed Components: A 36-Hour Forecast for a Site in Beijing by Taotao Lv, Yulu Yi, Zhuowen Zheng, Jie Yang, Siwei Li

“…To address this issue, this study constructs a hybrid prediction model integrating improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), bi-directional long short-term memory neural network (BiLSTM), and the persistence model to forecast the hourly ozone concentrations for the next continuous 36 h. …”
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Automatic XPath generation agents for vertical websites by LLMs by Jing Huang, Jie Song

“…The advent of large language models (LLMs) has introduced new possibilities for this task, enabling high-accuracy information extraction from individual pages. …”
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Gravitational edge mode in N $$ \mathcal{N} $$ = 1 Jackiw-Teitelboim supergravity by Kyung-Sun Lee, Akhil Sivakumar, Junggi Yoon

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Application of Improved Multi-Fractal Trend Removing Wave Model in the Analysis of Multi-Fractal Characteristics of Harmonic Signals by Jiebin Wen

“…To address this challenge, this paper constructs a novel method for analyzing the multi-fractal features of harmonic signals by integrating multi-fractal detrended fluctuation models, wavelet transform, and empirical mode decomposition techniques. …”
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On Analytical Solution of Time-Fractional Biological Population Model by means of Generalized Integral Transform with Their Uniqueness and Convergence Analysis by Saima Rashid, Rehana Ashraf, Ebenezer Bonyah

“…This research utilizes the generalized integral transform and the Adomian decomposition method to derive a fascinating explicit pattern for outcomes of the biological population model (BPM). …”
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Gaussian process modeling and multi-step prediction for time series data in wireless sensor network environmental monitoring by Yan CHEN, Zi-jian WANG, Ze ZHAO, Dong LI, Li CUI

“…For time series data collected from WSN environmental monitoring applications,a novel multi-step prediction method based on Gaussian process model was proposed.The method could make prediction for future environmental monitoring data.Kernel functions were used to describe data properties in the Gaussian process model.Kernel functions for environmental monitoring data were constructed through the EMD(empirical mode decomposition)technique and analysis of data inherent physical properties.And the constructed kernel functions were capable of describing the data change mode.Extensive experiments for multi-step prediction performance comparison test were performed on three kinds of data sets using over 20 000 environmental monitoring data records.Experimental results show that the average prediction accuracy of the Gaussian process multi-step prediction method can be increased by 20% than compared prediction methods.The prediction method can be applied to future environmental parameters trend analysis,early warning for abnormal environmental events and other scenes.…”
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Gaussian process modeling and multi-step prediction for time series data in wireless sensor network environmental monitoring by Yan CHEN, Zi-jian WANG, Ze ZHAO, Dong LI, Li CUI

“…For time series data collected from WSN environmental monitoring applications,a novel multi-step prediction method based on Gaussian process model was proposed.The method could make prediction for future environmental monitoring data.Kernel functions were used to describe data properties in the Gaussian process model.Kernel functions for environmental monitoring data were constructed through the EMD(empirical mode decomposition)technique and analysis of data inherent physical properties.And the constructed kernel functions were capable of describing the data change mode.Extensive experiments for multi-step prediction performance comparison test were performed on three kinds of data sets using over 20 000 environmental monitoring data records.Experimental results show that the average prediction accuracy of the Gaussian process multi-step prediction method can be increased by 20% than compared prediction methods.The prediction method can be applied to future environmental parameters trend analysis,early warning for abnormal environmental events and other scenes.…”
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Multiscale Sample Entropy-Based Feature Extraction with Gaussian Mixture Model for Detection and Classification of Blue Whale Vocalization by Oluwaseyi Paul Babalola, Olayinka Olaolu Ogundile, Vipin Balyan

“…To improve the accuracy of classification models, a GMM-based feature selection method is proposed, which evaluates both positively and negatively correlated features while considering inter-feature correlations. …”
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Recursive Time Series Prediction Modeling of Long-Term Trends in Surface Settlement During Railway Tunnel Construction by Feilian Zhang, Qicheng Wei, Zhe Wu, Jiawei Cao, Danlin Jian, Lantian Xiang

“…The accuracy of the on-site nonlinear regression fitting prediction method needs to be improved. To prevent surface settlement and surrounding rock collapse during railroad tunnel construction, while also ensuring the safety of the tunnel and existing structures, we propose a recursive prediction model for the long-term trend of surface settlement utilizing a singular spectrum analysis (SSA), improved sand cat swarm optimization (ISCSO), and a kernel extreme learning machine (KELM). …”
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