Models of the Impact of Socio-Economic Shocks on Higher Education Development by Olena Rayevnyeva, Volodymyr Ponomarenko, Silvia Matusova, Kostyantyn Stryzhychenko, Stanislav Filip, Olha Brovko

“…To assess the impact of socio-economic shocks on the HES, the time-series decomposition method and cross-spectral analysis were used. …”
Get full text

Modelling Friction-Induced Dynamic Instability Dedicated for Isogeometric Formulation by P. Mohanasundaram, K. Shimoyama, F. Gillot, S. Besset

“…In this case, the dynamical response of the system is implied to be sensitive to the contact stiffness modelled through the normal compliance approach. Typically, with the normal compliance approach, the continuum of the contact interface is approximated through a set of nonlinear springs which can be interpreted as a collocation method. …”
Get full text

Numerical Analysis of Fractional Order Epidemic Model of Childhood Diseases by Fazal Haq, Muhammad Shahzad, Shakoor Muhammad, Hafiz Abdul Wahab, Ghaus ur Rahman

“…The fractional order Susceptible-Infected-Recovered (SIR) epidemic model of childhood disease is considered. Laplace–Adomian Decomposition Method is used to compute an approximate solution of the system of nonlinear fractional differential equations. …”
Get full text

Influence maximization algorithm of social networks based on Transformer model by YU Shuke, YAO Yao, YAN Chenxue

“…Firstly, the high influential nodes of the society network were selected based on the k-shell decomposition method. Seconcly, the topology structure information and connection framework information of the candidate nodes were discovered by use of the random walk strategy. …”
Get full text

An Improved Kernel Entropy Component Analysis for Damage Detection Under Environmental and Operational Variations by Shuigen Hu, Jian Yang, Jiezhong Huang, Dongsheng Li, Cheng Li

“…To address these limitations, a novel damage detection method combining Variational Mode Decomposition (VMD) and Dynamic Kernel Entropy Component Analysis (DKECA) is proposed. …”
Get full text

Self-adaptive prediction and prewarning model of mine gas concentration by Dingwen Dong

“…Abstract In order to expand the function of safety monitoring and control system in coalmine, and realize the accurate real-time prediction and reliable prewarning of mine gas concentration, study the self-adaptive prediction and prewarning method for gas concentration based on Empirical Mode Decomposition (EMD) and Gaussian Process Regression (GPR). …”
Get full text

Regional Geomagnetic Field Modeling Based on Associated Legendre Polynomials by Libo Zhu, Houpu Li, Jineng Ouyang, Bo Zhu, Ming Chang

“…This model employs the associated Legendre polynomials method, which combines the QR decomposition approach and a comprehensive evaluation index formula to enhance the computational efficiency of parameter estimation. …”
Get full text

Formulating genome‐scale kinetic models in the post‐genome era by Neema Jamshidi, Bernhard Ø Palsson

“…While progress has been made with statistical and structural methods, large‐scale systems have remained refractory to dynamic model building by traditional approaches. …”
Get full text

Multi-model assessment and thermodynamic prediction for oxalate-tungstate complexes by Yong Liang, Ting Pu, Zanhong Chen, Yinliang Liu, Congyu Zhang

“…To address the critical bottleneck of lacking fundamental thermodynamic data in the development of a new process for dissolving scheelite hydrochloric acid decomposition residues using oxalic acid, this study systematically evaluated the predictive performance of the group contribution method, the similar system linear law method, as well as the electrostatic, Fuoss, and Bjerrum theoretical models in oxalate, carbonate, molybdate, and tungstate aqueous systems. …”
Get full text

Reviewing the complexity of endogenous technological learning for energy system modeling by Johannes Behrens, Elisabeth Zeyen, Maximilian Hoffmann, Detlef Stolten, Jann M. Weinand

“…Energy system components like renewable energy technologies or electrolyzers are subject to decreasing investment costs driven by technological progress. Various methods have been developed in the literature to capture model-endogenous technological learning. …”
Get full text

Personnel management on the basis of the competence model formation in lean production by G. V. Karamushko, N. G. Maskova

“…The purpose of the research is to develop and improve human resources of an organization by using a competence model in the field of lean production. The following methods are used: methods of generalization, comparative analysis, induction, decomposition, formalization, and modeling. …”
Get full text

Probing the Pitfalls: Understanding SVD’s Shortcomings in Language Model Compression by Сергей Александрович Плетенев

“…First, we chose a widely-used pre-trained model (Bert-base and Llama 2) as our baseline. Then, we applied low-rank factorization to its transformer layers using various singular value decomposition algorithms at different compression rates. …”
Get full text

Experimental Investigation on the Influence of the Location of Sand Mining on the Local Scour Characteristics of Bridge Piers by WU Wei, CAI Huiyi, WANG Hao, FU Dabao, CHEN Zetong, YAO Jiateng

Get full text

ANALYSIS OF MATHEMATICAL MODELS USED FOR ECONOMETRICAL TIME SERIES FORECASTING by D. A. Petrusevich

“…The further research is going to target the trend - seasonal - noise decomposition of time series. Statistical packages which are often in use have got different methods to compute the ARIMA coefficients. …”
Get full text

Chemical reaction mechanisms and models of energetic materials: A perspective by Li Meng, Qing-guan Song, Chuang Yao, Lei Zhang, Si-ping Pang

“…This perspective first presents both EMs’ reaction mechanisms revealed via multiscale simulations and experimental methods, including thermal decomposition, shock initiation, and post combustion. …”
Get full text

Ultra-Short-Term Photovoltaic Power Prediction Based on Predictable Component Reconstruction and Spatiotemporal Heterogeneous Graph Neural Networks by Yingjie Liu, Mao Yang

“…The proposed method is applied to a PV power plant in Gansu, China, and the results show that the prediction method based on the proposed combined spatio-temporal heterogeneous graph neural network model combined with the proposed predictable component extraction achieves an average reduction of 6.50% in the RMSE, an average reduction of 2.50% in the MAE, and an average improvement of 11.93% in the R² over the direct prediction method, respectively.…”
Get full text

Estimation of heat transfer parameters by using trained POD-RBF and Grey Wolf Optimizer by Minh Ngoc Nguyen, Nha Thanh Nguyen, Thien Tich Truong

“…In order to accelerate the process, the model order reduction technique Proper-Orthogonal-Decomposition (POD) is used. …”
Get full text

Short-Term Power Load Prediction of VMD-LSTM Based on ISSA Optimization by Shuai Wu, Huafeng Cai

“…To address the challenges of fluctuating power loads and inaccurate predictions by conventional methods, this paper presents a novel hybrid framework combining Variational Mode Decomposition (VMD), Long Short-Term Memory (LSTM), and the Improved Sparrow Search Algorithm (ISSA). …”
Get full text

Autoencoder Extreme Learning Machine for Fingerprint-Based Positioning: A Good Weight Initialization is Decisive by Darwin P. Quezada Gaibor, Lucie Klus, Roman Klus, Elena Simona Lohan, Jari Nurmi, Mikko Valkama, Joaquin Huerta, Joaquin Torres-Sospedra

Get full text

Drought prediction based on an improved VMD-OS-QR-ELM model. by Yang Liu, Li Hu Wang, Li Bo Yang, Xue Mei Liu

“…Finally, VMD and OS-QR-ELM were combined to construct a drought prediction method based on the VMD-OS-QR-ELM. The reliability and accuracy of the VMD-OS-QR-ELM model were improved by 86.19% and 93.20%, respectively, compared with those of the support vector regression model combined with empirical mode decomposition. …”
Get full text