Research on predicting the thermocompression deformation behavior of Mg–Li matrix composite using machine learning and traditional techniques by Dandan Li, Xiaoyu Hou, Yangfan Liu, Linhao Gu, Jinhui Wang, Jiaxuan Ma, Xiaoqiang Li, Zhi Jia, Qichi Le, Dexue Liu, Xincheng Yin

“…Then, the thermal compression flow behavior of the as-cast composite was comparatively researched using a traditional Arrhenius model and advanced machine learning methods (Linear Regression, AdaBoost, Random Forest, and XGBoost). …”
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Research on Annual Runoff Prediction Based on EMD-LSTM-ANFIS Model by HU Shunqiang, CUI Dongwen

“…To improve the accuracy of runoff prediction,this paper proposes a runoff prediction model based on the combination of empirical mode decomposition (EMD),long short-term memory (LSTM) neural network,and adaptive neuro-fuzzy inference system (ANFIS),decomposes the original runoff sequence into multiple regular component sequences through EMD,and reconstructs the phase space of each component sequence by the autocorrelation function method (AFM) and the false nearest neighbor method (FNN) to determine the input and output vectors,establishes the EMD-LSTM-ANFIS prediction model,and constructs the EMD-LSTM,EMD-ANFIS,LSTM,ANFIS as comparison models,as well as predicts and compares the annual runoff of the Longtan Station in Yunnan Province by the five models.The results show that the average relative error of the EMD-LSTM-ANFIS model for the annual runoff prediction is 3.18%,which is reduced by 55.0%、65.2%、68.1%、78.4% compared with the EMD-LSTM,EMD-ANFIS,LSTM,and ANFIS models respectively,with higher prediction accuracy and stronger generalization ability.Therefore,the EMD-LSTM-ANFIS model is feasible and reliable for runoff prediction.…”
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Simulation and Experimental Research on Composite Diaphragm Hydraulic Force/Displacement Amplification Mechanism with Adjustable Initial Volume by Yong Yang, Tingyu Geng, Zengmeng Zhang, Jiaoyi Hou, Dayong Ning, Yongjun Gong

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Anti-inflammatory action and intraocular kinetics of bromfenac in anterior uveitis depending on the composition of topical formulation by E. V. Blinova, P. A. Lyabushev, E. A. Litvin, D. S. Blinov, A. A. Galchin, M. V. Shikh, I. S. Struts, K. D. Blinov, S. D. Yudina, O. V. Vasilkina, S. E. Zotov, E. V. Shikh

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APPLICATION OF THE COPULA METHOD TO ANALYZE THE RELATIONSHIPS OF MACROECONOMIC FACTORS AFFECTING THE CSPI by Sri Endang Saleh, Debyyansa Pakaya, Irsan K. Hasan, Ismail Djakaria

“…In this study, dependency analysis was carried out with the Copula approach method involving the Tau Kendal method for parameter estimation and the Maximum Likelihood Estimation (MLE) method to choose the best Copula model to explain the relationship between the Composite Stock Price Index and these macroeconomic factors. …”
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Experience in modeling inclined cracks in materials with cubic crystal structure by Karina A. Mushankova, Larisa V. Stepanova

“…The atomic stress distributions associated with the crack tip are obtained using the molecular dynamics method. Continuum distributions are obtained from the theoretical solution of the problem of determining the stress-strain state at the crack tip, based on the methods of the elasticity theory of anisotropic media and the subsequent decomposition of complex potentials by eigenfunctions. …”
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Models, systems, networks in economics, engineering, nature and society by S.I. Noskov, E.S. Popov

“…The approach described in the work allows us to combine the advantages of the least modulus and anti-robust estimation methods when modeling. A regression model of freight turnover of road transport in the Russian Federation has been constructed that is adequate to the analyzed object. …”

« Décomposition fécondante » : la chimie organique et les savoirs du vivant chez Flaubert by Judith Wulf

“…Flaubert, who does not escape this tendency, involves a wide assortment of natural sciences in his writings, which belongs to a realistic approach, whereas chemistry refers rather to abstract modeling. While the natural sciences are associated with an analytical perspective founded on dissection, chemistry has more to do with composition. …”
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Comparison of soil eDNA to camera traps for assessing mammal and bird community composition and site use by Sasha J. Tetzlaff, Aron D. Katz, Patrick J. Wolff, Matthew E. Kleitch

“…We also used Bayesian spatial occupancy models for two widely distributed game species (white‐tailed deer, Odocoileus virginianus, and ruffed grouse, Bonasa umbellus) that were moderately detected with both survey methods and found species‐specific site use (occupancy) estimates were similar between cameras and eDNA analysis. …”
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Fault Feature Research of Rolling Bearing based on Empirical Mode Decomposition and Principle Component Analysis by Zheng Xin

“…It is proposed that a fault diagnosis method for rolling bearing based on empirical mode decomposition（ EMD） and multivariate statistical process control（ MSPC）,the Hilbert- Huang transformation and principal component analysis（ PCA） are combined effectively in this method. …”
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Prediction of the Remaining Useful Life of Lithium–Ion Batteries Based on Mode Decomposition and ED-LSTM by Bingzeng Song, Guangzhao Yue, Dong Guo, Hanming Wu, Yonghai Sun, Yuhua Li, Bin Zhou

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A novel method for predicting the geochemical composition of tailings with laboratory field and hyperspectral airborne data using a regression and classification-based approach by Yaron Ogen, Michael Denk, Cornelia Glaesser, Holger Eichstaedt

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Complex, Temporally Variant SVD via Real ZN Method and 11-Point ZeaD Formula from Theoretics to Experiments by Jianrong Chen, Xiangui Kang, Yunong Zhang

“…Then, by using the real zeroing neurodynamics (ZN) method, matrix vectorization, Kronecker product, vectorized transpose matrix, and dimensionality reduction technique, a dynamical model, termed the continuous-time SVD (CTSVD) model, is derived and investigated. …”
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Research on Multipoint Leak Location of Gas Pipeline Based on Variational Mode Decomposition and Relative Entropy by Yongmei Hao, Zhanghao Du, Juncheng Jiang, ZhiXiang Xing, Xinming Yan, Shuli Wang, Yongchao Rao

“…A multipoint leak detection and location method for urban gas pipelines based on variational mode decomposition and relative entropy was proposed. …”
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The Impact of Velocity Update Frequency on Time Accuracy for Mantle Convection Particle Methods by S. J. Trim, S. L. Butler, R. J. Spiteri

“…This has implications for particle methods used to model the advection of quantities such as temperature or composition. …”
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Tensor decomposition based-joint active device detection and channel estimation under frequency offset by QU Ruiyun, LIU Zujun, HUANG Beilei

“…In order to avoid the non-convexity introduced by the nonlinear between the frequency offsets and the channels, firstly, tensor decomposition was used to model the received signal from the perspective of the preamble sequence, channel, and frequency offset. …”
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Optimizing Bioceramic Composites for Hip Joint Replacements using SPS Method: Investigating the Effects of Titanium Diboride (TiB2) on Tribological Properties by Pavankumar Ravikumar, Goud Mallesh, S. Suresh Kumar, H. S. Manjunatha

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Application of Empirical Mode Decomposition with Local Linear Quantile Regression in Financial Time Series Forecasting by Abobaker M. Jaber, Mohd Tahir Ismail, Alsaidi M. Altaher

“…We propose a two-stage technique that combines the empirical mode decomposition (EMD) with nonparametric methods of local linear quantile (LLQ). …”
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Prediction of Dissolved Gas Concentration in Transformer Oil Based on Hybrid Mode Decomposition and LSTM-CNN by Tie CHEN, Zhifan ZHANG, Xianshan LI, Yifu CHEN, Hongxin LI

“…Predicting the concentration of dissolved gas in oil can help to know in advance the operation trend of transformers. A prediction method is thus proposed based on hybrid mode decomposition and LSTM-CNN network to achieve accurate gas concentration prediction. …”
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Time Series Prediction of Aerodynamic Noise Based on Variational Mode Decomposition and Echo State Network by Zhoufanxing Lei, Haiyang Meng, Jing Yang, Bin Liang, Jianchun Cheng

“…Due to the significant dynamical and non-stationary characteristics of aerodynamic noise, it is challenging to precisely predict its temporal behavior. Here, we propose a method combining variational mode decomposition (VMD) and echo state network (ESN) to accurately predict the time series of aerodynamic noise induced by flow around a cylinder. …”
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