Clues to seismic data interpretation within the zones of the sand injections in so called "anomalous section" of the Bazhenovo Black Shales formation on the examples of the Potochn... by Gatina Nadezhda, Sarieva Marina, Mukhutdinova Oksana, Popkov Andrey, Gavrilov Sergey

“…The paper describes the application of the spectral decomposition method for detailing the structure of anomalous sections zones of the Bazhenovo Formation or in another words Giant Sand injection Complex (GSIC) of the Ob river region. …”
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Analytical Models for the Time Response of a Microstrip Line with Two Additional Symmetrical Conductors on Top under Different Boundary Conditions at Their Ends by A. Sekenova, Z. M. Kenzhegulova, I. Y. Sagiyeva, T. R. Gazizov

“…Therefore, comparison of time responses obtained by numerical methods and analytical models appears an important research task.   …”
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A Global Irradiance Prediction Model Using Convolutional Neural Networks, Wavelet Neural Networks, and Masked Multi-Head Attention Mechanism by Walid Mchara, Lazhar Manai, Mohamed Abdellatif Khalfa, Monia Raissi, Salah Hannechi

“…Existing approaches, including statistical methods, conventional machine learning models, and standalone deep learning techniques like LSTM, fail to integrate local features and long-term dependencies simultaneously, creating a need for more robust solutions. …”
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Long-term comparative analysis of machine learning models: A deep dive into applications of artificial intelligence for enhancing photovoltaic performance prediction by Ali Akbar Yaghoubi, Mahdi Gandomzadeh, Aslan Gholami, Roghayeh Gavagsaz-Ghoachani, Majid Zandi

“…Six supervised machine learning models were trained: K-Nearest Neighbors (KNN), Cross-Decomposition Regression, Decision Trees, Support Vector Regression (SVR), Multi-Layer Perceptron (MLP), and Ensemble Learning. …”
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Enhanced Short-Term PV Power Forecasting via a Hybrid Modified CEEMDAN-Jellyfish Search Optimized BiLSTM Model by Yanhui Liu, Jiulong Wang, Lingyun Song, Yicheng Liu, Liqun Shen

“…This study proposes a novel hybrid forecasting model that integrates complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), the jellyfish search (JS) optimization algorithm, and a bidirectional long short-term memory (BiLSTM) neural network. …”
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Fast dynamical simulation combining harmonic-modal hybrid formulations with space separated representations by Claudia Germoso, Sebastian Rodriguez, Angelo Pasquale, Francisco Chinesta

“…These examples highlight the method's capability to handle high-resolution 3D problems efficiently, reducing it to a sequence of 1D or 2D problems, enabling significant computational time savings compared to the Finite Element Method (FEM).…”
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Evaluating the efficiency of environmentally friendly magnetic photocatalyst for the treatment of industrial effluents containing dye pollutants by Sedigheh Abbasi

“…Also, the Box–Cox curve confirms the adequacy of the statistical models without any transformation function.…”
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Compliance of the Accounting System with the Natural Classification Requirements by A. E. Kovalev

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Study on the interaction mechanism between Shanghai Port throughput and urban economy by Xuanchao Cai

“…The Structural Vector Autoregressive (SVAR) model alongside cointegration tests, Granger causality tests and variance decomposition methods were also employed for empirical analysis. …”
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Upgoing and Downgoing Wavefield Separation in Vertical Seismic Profiling Guided by Signal Knowledge Representation by Cai Lu, Liyuan Qu, Jijun Liu, Jianbo Gao

“…This study introduces a VSP wave-separation method using signal knowledge representation, primarily by constructing knowledge representations of upgoing and downgoing waves. …”
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Model Biokinetika Sistem Kontak Stabilisasi Lumpur Air Lindi Berdasarkan Pengaruh Fosfor dan Variasi Waktu Detensi Unit Kontak by Muhammad Faiz Kahendran, Owen Jacob Notonugroho, Chusnul Arif, Ariani Dwi Astuti, Allen Kurniawan

“…Berdasarkan metode statistika, model estimasi konsentrasi COD efluen tangki kontak terbaik adalah model dari model JST. …”
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Ensemble reconstruction of missing satellite data using a denoising diffusion model: application to chlorophyll <i>a</i> concentration in the Black Sea by A. Barth, J. Brajard, A. Alvera-Azcárate, B. Mohamed, C. Troupin, J.-M. Beckers

“…In this paper, we investigate the use of a denoising diffusion model to reconstruct missing observations. Such methods can naturally provide an ensemble of reconstructions where each member is spatially coherent with the scales of variability and with the available data. …”
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A Novel Fault Diagnosis Model for Bearing of Railway Vehicles Using Vibration Signals Based on Symmetric Alpha-Stable Distribution Feature Extraction by Yongjian Li, Weihua Zhang, Qing Xiong, Tianwei Lu, Guiming Mei

“…Then a new statistical method of feature extraction, symmetric alpha-stable distribution, is employed to obtain representative features from intrinsic mode functions. …”
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Prediction of Remaining Useful Life of Packing Sets in a Plunger-Type High-Pressure Compressor Based on the PCA/SVD Analysis and NN Model by Jin-Wei Liang, Shyh-Chin Huang, Chun-Ling Lin

“…In order to enhance the prediction accuracy of the RUL of high-pressure packing, a linear regression algorithm and a two-term power series regression algorithm are both integrated into the NN (neural network) model. The effectiveness of the method is examined using the averaged difference (over 13 data sets) between predicted and real failure events. …”
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Open-Phase Fault Tolerant Model Predictive Current Controller for Asymmetrical Dual Three-Phase Permanent Magnet Synchronous Machine Drive System by Adriano Navarro-Temoche, Josu Jugo, Edorta Ibarra, Inigo Kortabarria, Endika Robles

“…Multiple-Input Multiple-Output (MIMO) tools are used to tune the controller in the theoretical analysis, supported by the disk margin method. The aim of this work is to provide an MPC-based solution with the same functionalities as of the conventional PI-R based fault tolerant control method. …”
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Global trends and future predictions of gastrointestinal ulcers in youth by Kun He, Kun He, Shicai Ye, Yanqi Kou, Yanqi Kou, Shenshen Du, Weinan Yuan, Lei Ge, Yuan Tian, Botao Luo, Yanping Ha, Liping Zhan, Ruyin Ye, Yujie Huang, Bingbing Li, Biao Nie, Yuping Yang

“…The data were then stratified by age, gender, and economic development level. We applied decomposition analysis and frontier analysis, and compared the performance of two statistical prediction models. …”
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The Long-Term Surface Deformation Monitoring and Prediction of Hutubi Gas Storage Reservoir in Xinjiang Based on InSAR and the GWO-VMD-GRU Model by Wang Huang, Wei Liao, Jie Li, Xuejun Qiao, Sulitan Yusan, Abudutayier Yasen, Xinlu Li, Shijie Zhang

“…This research aims to ensure the stable and efficient operation of the facility through long-term monitoring, using remote sensing data and advanced modeling techniques. The study employs the SBAS-InSAR method, leveraging Synthetic Aperture Radar (SAR) data from the TerraSAR and Sentinel-1 sensors to observe displacement time series from 2013 to 2024. …”
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Global, regional, and national burden of IHD attributable to PM pollution aged 70 and above: an age-period-cohort modeling and frontiers analysis study by Ke-Jie He, Haitao Wang, Xu Liu, Rongying Yang, Guoyu Gong

“…Joinpoint regression assessed long-term trends, Age-Period-Cohort modeling evaluated demographic drivers, and decomposition analysis identified the contributions of population growth, aging, and epidemiological changes. …”
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Study on the Combustion Behavior and Kinetic Characteristics of Semi-Coke from Oil Shale by Fajun Zhao, Lei Zhang, Sen Liu, Tianyu Wang, Peiyong Xue, Mingxuan Wu, Jiankang Yun

“…Thermogravimetric analysis (TGA) experiments, combined with both model-free and model-based methods, were used to explore the thermal characteristics, kinetic parameters, and reaction mechanisms of the combustion process. …”
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Simulation of discrete control systems with parallelism of behavior by D. I. Cheremisinov, L. D. Cheremisinova

“…A method is proposed for transforming the description of an algorithm in the language into a TLM model, which is based on the representation of language operations as compositions of elementary operations that are performed sequentially. …”
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