MODELLING FLUCTUATIONS OF GROUNDWATER LEVEL USING MACHINE LEARNING ALGORITHMS IN THE SOKOTO BASIN by Samson Alfa, Haruna Garba, Augustine Odeh

“…This included removing null values, interpolating missing data and downsampling to weekly intervals engineering to improve model performance. Time series decomposition and the creation of lag features were also utilized to capture temporal dependencies effectively. …”
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A turbulence reduced order model based on non-interpolated convolutional autoencoder by WU Pin, ZHANG Bo, SONG Chao, ZHOU Zhu

“…Reduced-order modeling stands as a pivotal method in curbing the computational expenses linked with expansive fluid dynamics quandaries by employing proxy numerical simulations. …”
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APPLICATION OF MODELS OF INFORMATION AND ANALYTICAL SUPPORT SYSTEMS FIRE FIGHTING RESCUE UNITS by O. I. Stepanov, S. A. Khudyakova

“…Objectives It was proposed to review the structure of the fire and rescue divisions management system, based on the decomposition of the forces and means of the subdivisions into fire extinguishing positions and ensuring fire extinguishing actions.Method The structural and functional model of the development of the fire and rescue divisions management system has been clarified, which allows to present the stages of the development of the system as components of a single fire extinguishing process. …”
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Carbon emission forecasting in Zhejiang Province based on LASSO algorithm and grey model by HONG Jingke, DU Wei, SHAO Jin*, LAO Huimin

“…First, the variable mode decomposition method is used to decompose the historical data of carbon emissions in Zhejiang Province, enabling an analysis of its cyclicality fluctuations. …”
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Method for EEG signal recognition based on multi-domain feature fusion and optimization of multi-kernel extreme learning machine by Shan Guan, Tingrui Dong, Long-kun Cong

“…Secondly, multivariate autoregressive (MVAR) model, wavelet packet decomposition, and Riemannian geometry methods are used to extract features from the time domain, frequency domain, and spatial domain, respectively, to construct a joint time-frequency-space feature vector. …”
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A Method for Predicting the Remaining Life of Lithium-Ion Batteries Based on an Improved Dempster–Shafer Evidence Theory Framework by Tongrui Zhang, Hao Sun

“…This paper proposes a RUL prediction method for lithium-ion batteries based on an improved Dempster–Shafer (D-S) evidence theory framework, which aims to improve the accuracy and robustness of prediction by integrating the advantages of a wavelet packet decomposition convolutional neural network (WPD-CNN) and an extended Kalman filter (EKF). …”
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A New Heuristic Solution Method for Maximal Covering Location-Allocation Problem with M/M/1 Queueing System by F. Moeen Moghadas

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A Review of Health Monitoring and Model Updating of Vibration Dissipation Systems in Structures by Neda Godarzi, Farzad Hejazi

“…Additionally, the review highlights the evolution of SHM and model updating techniques, distinguishing groundbreaking advancements from established methods. …”
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Predictive Modeling of Covid-19 Data in the US: Adaptive Phase-Space Approach by Vasilis Z. Marmarelis

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Collaborative optimization of photovoltaic and energy storage devices in urban and rural distribution networks based on the target cascade analysis method by WANG Qiming, XIA Kun, JIAO Pingyang, ZHANG Peijie, DONG Jinlong, LI Peng

“…Second， the decomposition modeling is applied to decouple the collaborative planning model， and the target cascade analysis method is used for distributed parallel iterative solving. …”
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Modeling of Ionization and Recombination Processes in Plasma with Arbitrary Non-Maxwellian Electron Distribution by Chengcai Shen, Xiaocan Li, Yuan-Kuen Ko, John C. Raymond, Fan Guo, Vanessa Polito, Viviane Pierrard

“…In this work, we report two methods for fitting various non-Maxwellian distributions by using the Maxwellian decomposition strategy. …”
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Context-Defined Model of Open Systems Interaction for IoT Cybersecurity Issues Study by Victor Tikhonov, Eduard Siemens, Yevhen Vasiliu, Valery Sitnikov, Abdullah Taher, Olena Tykhonova, Kateryna Shulakova, Serhii Tikhonov

“…As an example, a particular local version of the S-CDM model is considered in the form of six independent tasks for AI-aided methods of cybersecurity provision. …”
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Metro Foundation Pit Deformation Prediction Method Based on CNN-GRU Neural Network under Incomplete Data Condition by ZHOU Yi, WANG Zhangqiong, ZOU Yuangeng, CAI Yonghui, XU Xiaoya, ZHAO Qilin

“…[Method] A data sample set is constructed using incomplete foundation pit deformation monitoring data and missing monitoring data from nearby monitoring points, and then input into the CNN model to complete data imputation and obtain continuous and complete monitoring data. …”
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Software Control of the Movement of a Differential Drive Robot for Different Friction Models by M. S. Salimov, I. V. Merkuryev

“…When visualizing the models under study, the built-in numerical methods of the Wolfram Mathematica system were used with a minimum accuracy of 10-6.Results. …”
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Research on the Rapid Detection of Formaldehyde Emission From Wood-Based Panels Based on the AMSHKELM by Yinuo Wang, Huanqi Zheng, Hua Wang, Yucheng Zhou

“…To enable quick and accurate detection of formaldehyde emissions from wood-based panels and to address the complexities of the full-scale chamber method and the inaccuracy of sensor-based methods, a modified formaldehyde emission model based on AdaBoost-MSBKA-SVMD-HKELM (AMSHKELM) is proposed. …”
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A Method for Extracting Features of the Intrinsic Mode Function’s Energy Arrangement Entropy in the Shaft Frequency Electric Field of Vessels by Xiaoguang Ma, Zhaolong Sun, Runxiang Jiang, Xinquan Yue, Qi Liu

“…To address the challenge of detecting low-frequency electric field signals from vessels in complex marine environments, a vessel shaft frequency electric field feature extraction method based on intrinsic mode function energy arrangement entropy values is proposed, building upon a scaled model. …”
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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

“…However, the analysis related to this issue is not available.MethodsFor estimation purposes, the Augmented Dickey-Fuller (ADF) test, Vector Autoregressive (VAR) model, Granger causality tests, Impulse Response Function (IRF), Variance Decomposition (VDC), and Vector Error Correction Model (VECM) are employed.ResultsRainfall has a significant impact on dengue incidence compared to temperature and humidity. …”
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Model of a Parallel-Pipeline Computational Process for Solving a System of Grid Equations by V. N. Litvinov, N. B. Rudenko, N. N. Gracheva

“…The research objective was to create a model of a parallel-conveyor computational process for solving a system of grid equations by a modified alternating-triangular iterative method using the decomposition of a three-dimensional uniform computational grid that takes into account technical characteristics of the equipment used for calculations.Materials and Methods. …”
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Large Area Crops Mapping by Phenological Horizon Attention Transformer (PHAT) Method Using MODIS Time-Series Imagery by Quanshan Gao, Taixia Wu, Hongzhao Tang, JingYu Yang, Shudong Wang

“…To address these challenges, this article developed an advanced deep learning crop mapping method, i.e., phenological horizon attention mechanism-transformer model (PHAT) to achieve rapid and accurate multiple crops extraction over large areas. …”
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Short-term Wind Power Forecasting Based on BWO‒VMD and TCN‒BiGRU by LU Jing, ZHANG Yanru, WANG Rui

“…The experimental results indicated that applying this series of methods improves the prediction accuracy. Its capacity to manage complex time series data is demonstrated, and the advancement and innovation of algorithms and models are supported. …”
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