Functional Data Analysis in Forecasting Serbian Fertility by Vladimir Nikitović

“…One of the most important benefits of the method reflected in confirmation that is essentially to model and forecast more than one principal component in order to adequately address sources of variation in fertility. …”
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The Numerical Investigation of Fractional-Order Zakharov–Kuznetsov Equations by Pongsakorn Sunthrayuth, Farman Ali, A. A. Alderremy, Rasool Shah, Shaban Aly, Y. S. Hamed, Jeevan Katle

“…In this article, a modified method called the Elzaki decomposition method has been applied to analyze time-fractional Zakharov–Kuznetsov equations. …”
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Two-Phase Flow in Wire Coating with Heat Transfer Analysis of an Elastic-Viscous Fluid by Zeeshan Khan, Rehan Ali Shah, Saeed Islam, Bilal Jan

“…The analytical solution of the theoretical model is obtained by Optimal Homotopy Asymptotic Method (OHAM). …”
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Data-Driven Identification of Gas Turbine Engine Dynamics via Koopman Operator Genetic Algorithm by David Grasev

“…Linear parameter-varying and bilinear Koopman models were considered. Extended dynamic mode decomposition was employed to obtain a finite-dimensional approximation of the operator. …”
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Advances in Electroencephalography for Post-Traumatic Stress Disorder Identification: A Scoping Review by Jose A. Salazar-Castro, Diego H. Peluffo-Ordonez, Diego M. Lopez

“…Broader datasets representing diverse populations are essential to mitigate bias and facilitate robust inter-model comparisons. Future research should focus on deep learning, adaptive signal decomposition, and multimodal approaches.…”
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PINN based on multi-scale strategy for solving Navier–Stokes equation by Shirong Li, Shaoyong Lai

“…Combining the framework and the idea of multi-scale methods in traditional numerical methods, such as domain decomposition and collocation self-adaption, we construct a method of the Physics-Informed Neural Networks (PINNs) based on multi-scale strategy to solve Navier–Stokes equations, and the results are more effective than XPINNs and SAPINNs. …”
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Robust interference alignment algorithm for cognitive MIMO interference network by Shi-lei ZHU, You ZHOU, Xiu-kun REN, Han-ying HU

“…A robust interference alignment algorithm was proposed for underlay cognitive MIMO interference network with imperfect channel-state information (CSI).Firstly,imperfect CSI was characterized by Euclidean ball-shaped uncer-tainty,based on which the optimization model of transmitting precoding and receiving interference subspace matrix was constructed with aimed of minimizing interference leak Then,primary users' interference temperature constraint un-der the worst-case condition was derived according to the matrix norm inequality.Finally,alternate iteration expressions of transceiver matrixes were obtained exploiting Lagrange partial dual-decomposition theory and sub-gradient update method.Moreover,the proposed algorithm's application condition and degrees of freedom range were theoretically ana-lyzed.Simulation results show that the proposed algor m is robust and its secondary users' network performance out-performs existing algorithms'.…”
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Vibroacoustic analysis of a clamped finite orthotropic laminated double-composite plate with an air cavity by Tran Ich Thinh, Pham Ngoc Thanh

“… The vibroacoustic analysis of a clamped finite orthotropic laminated double-composite plate with a closed air cavity is investigated analytically presented within classical laminated plate theory for laminated composite plate. Using the method of modal decomposition, a double Fourier series solution is obtained to characterize the vibroacoustic performance of the structure. …”
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A synergistic approach for enhanced eye blink detection using wavelet analysis, autoencoding and Crow-Search optimized k-NN algorithm by M. Chandralekha, N. Priyadharshini Jayadurga, Thomas M. Chen, Mithileysh Sathiyanarayanan, Kasif Saleem, Mehmet A. Orgun

“…This optimization method actively samples the search space to balance exploration and exploitation to identify the optimal configuration for the model. …”
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Efficient room-level heat load prediction in buildings using spatiotemporal distribution characteristics by Xin Tan, Kaixuan Xu, Yahui Wang, Qihui Yu, Yongheng Yu, Guoxin Sun

“…This study proposes a prediction method integrating spatiotemporal distribution features within a “global prediction + feature decomposition” framework to overcome traditional data-driven limitations. …”
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Tool wear prediction based on XGBoost feature selection combined with PSO-BP network by Zhangwen Lin, Yankun Fan, Jinling Tan, Zhen Li, Peng Yang, Hua Wang, Weiwei Duan

“…Subsequently, time-domain, frequency-domain, and time–frequency domain features are extracted from the preprocessed data using FFT and wavelet packet decomposition, followed by feature screening for tool wear mapping via Pearson correlation and XGBoost feature importance analysis as model input. …”
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Global, regional and national mortality burden of laryngeal cancer attributable to occupational exposure to sulfuric acid and asbestos: 1990–2021 and projections to 2040 by Xin Gong, Yinxia Xu, Yong Hao, Meitao Yi, Chao Yuan, Zhenhong Zheng, Jia Gong, Gongjie Shen, Yongqi Dong

“…Decomposition analysis was used to identify the drivers of disease burden changes. …”
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Thermoanalytical and Kinetic Studies for the Thermal Stability of Emerging Pharmaceutical Pollutants Under Different Heating Rates by Christian Ebere Enyoh, Tochukwu Oluwatosin Maduka, Miho Suzuki, Senlin Lu, Qingyue Wang

“…The kinetics of thermal degradation were analyzed using both model-fitting (Coats–Redfern (CR)) and model-free (Kissinger–Akahira–Sunose (KAS), Flynn–Wall–Ozawa (FWO), and Friedman (FR)) methods. …”
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Investigation of ACS image stabilization of on-board optoelectronic guidance and tracking devices by K. A. Burdinov, K. M. Shashkina, Ehsan Shaghaei

“…Lagrange equations of the second kind and the mixed Gilbert method made it possible to obtain a mathematical model of the CO OED. …”
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EXPERIMENTAL IDENTIFICATION OF AN ELASTO-MECHANICAL MULTI-DEGREE-OF-FREEDOM-SYSTEM USING STOCHASTIC SIGNALS by Simon Schleiter, Okyay Altay, Sven Klinkel

“…Relevant methods for this identification use Frequency Domain Decomposition (FDD), Autoregressive Moving Average Models (ARMA) and the Autoregressive Models with eXogenous input (ARX). …”
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Burden of melanoma in China and its provinces from 1990 to 2021: an analysis for the Global Burden of Disease Study 2021 by Lingling Yu, Fanshu Yan, Jinlei Qi, Lijun Wang, Maigeng Zhou, Peng Yin

“…A decomposition method was used to attribute changes in total deaths and DALYs to three explanatory components: population growth, population aging, and change of age-specific rates.ResultsOver the past 30 years, the age-standardized incidence rate (ASIR) of melanoma in China has shown an upward trend. …”
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Learning Random Access Schemes for Massive Machine-Type Communication With MARL by Muhammad Awais Jadoon, Adriano Pastore, Monica Navarro, Alvaro Valcarce

“…Moreover, the robustness of the proposed method in terms of scalability is also shown through simulations.…”
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HDN-DDI: a novel framework for predicting drug-drug interactions using hierarchical molecular graphs and enhanced dual-view representation learning by Jinchen Sun, Haoran Zheng

“…Future research will focus on refining decomposition rules as well as integrating external knowledge while preserving the model’s generalization capabilities.…”
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Global, regional, and national burden of older adult atopic dermatitis in 204 countries and territories worldwide by Yi Ou, Xinyi Shao, Jingbo Zhang, Jin Chen

“…We used joinpoint regression analysis, decomposition analysis, cross-country inequality analysis, frontier analysis and prediction model to epidemiological analysis.ResultsFrom 1990 to 2021, the global prevalence of older adult AD increased to 11,009,630 cases (95% UI: 9,915,829 to 12,170,941), even as ASRs declined, which were primarily driven by population growth. …”
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Exploring New Paradigms in Time Series Prediction by Integrating Computer Simulations and Machine Learning by Pengcheng Wu, Yan Shi, Pengfei Zhao, Zhengzhao Gu

“…Time series prediction is a challenging task that requires modeling complex temporal dependencies and structural priors. …”
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