Elevator fault precursor prediction based on improved LSTM-AE algorithm and TSO-VMD denoising technique. by Hao Cao, Xiaoyan Du

“…This study proposes an advanced elevator fault precursor prediction method integrating Variational Mode Decomposition (VMD), Bidirectional Long Short-Term Memory (BILSTM), and an Autoencoder with an Attention Mechanism (AEAM), collectively referred to as the VMD-BILSTM-AEAM algorithm. …”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction by Irfan Pathan, Arif Raza, Adarsh Sahu, Mohit Joshi, Yamini Sahu, Yash Patil, Mohammad Adnan Raza, Ajazuddin

“…This review explores the integration of AI techniques, including machine learning (ML), deep learning (DL), and generative models with traditional computational methods such as molecular docking, quantum mechanics, and molecular dynamics simulations. …”
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Existence of Solutions to Fractional Differential Equations with Mixed Caputo–Riemann Derivative by Mahir Almatarneh, Sonuc Zorlu, Nazim I. Mahmudov

“…The study of fractional differential equations is gaining increasing significance due to their wide-ranging applications across various fields. Different methods, including fixed-point theory, variational approaches, and the lower and upper solutions method, are employed to analyze the existence and uniqueness of solutions to fractional differential equations. …”
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Combining diffusion and transformer models for enhanced promoter synthesis and strength prediction in deep learning by Xin Lei, Xing Wang, Guanlin Chen, Ce Liang, Quhuan Li, Huaiguang Jiang, Wei Xiong

“…The effectiveness of our method was validated using data sets of Escherichia coli and cyanobacteria promoters, showing more stable and prompt convergence and more natural-like promoters than the variational autoencoder model. …”
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HyQ2: A Hybrid Quantum Neural Network for NextG Vulnerability Detection by Yifeng Peng, Xinyi Li, Zhiding Liang, Ying Wang

“…The proposed HyQ2 is integrated with graph-embedded and quantum variational circuits to validate and detect vulnerabilities from the 5G system's state transitions based on graphs extracted from log files. …”
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A Survey on Extremal Problems of Eigenvalues by Ping Yan, Meirong Zhang

“…To solve these extremal problems, we will reveal some deep results on the dependence of eigenvalues on potentials. Moreover, the variational method for the approximating extremal problems on the balls of the spaces Lα([0,1],ℝ), 1<α<∞ will be used. …”
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Multifractal-Aware Convolutional Attention Synergistic Network for Carbon Market Price Forecasting by Liran Wei, Mingzhu Tang, Na Li, Jingwen Deng, Xinpeng Zhou, Haijun Hu

“…This study pioneers the interdisciplinary integration of fractal theory and artificial intelligence methods for complex engineering analysis, enhancing the accuracy of carbon market price prediction. …”
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Research on Virtual Color Restoration of Complex Building System Based on Discrete Wavelet Transform by Chunqiao Song, Xutong Wu

“…According to the established model, the Euler–Lagrange equation is derived by the variational method, the corresponding diffusion equation is established, and the model is analyzed and numerically solved in detail to obtain the restored image. …”
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Deep VMD-attention network for arrhythmia signal classification based on Hodgkin-Huxley model and multi-objective crayfish optimization algorithm. by Hang Zhao, Xiongfei Yin

“…A multi-objective optimization method based on non-dominated sorting was integrated into the crayfish optimization algorithm (MOCOA). …”
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Exact Nonlinear Spectral Analysis of Nonsmooth WENO-JS Solutions by Tamer H. M. A. Kasem

“…The overdamping of the combination of WENO-JS with the popular third-order total variation diminishing Runge-Kutta method is discovered. …”
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A data-driven reduced-order model for fast prediction of resonant acoustic flow under vertical vibration based on secondary decomposition by Yuqi Gao, Ning Ma, Shifu Zhu, Pengchao Zhang, Hongxing Liu, Zhongyuan Xie

“…By integrating secondary decomposition techniques commonly used in time series prediction with ROM technology, this paper presents a non-intrusive flow field prediction method. …”
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Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm by Xiaoshi Zhuang, Honglue Wan, Dongran Song, Xinyu Fan, Yuchen Wang, Qian Huang, Jian Yang

“…Secondly, the seagull optimization algorithm is enhanced by integrating three strategies: the nonlinear adjustment strategy for control factors, the Gaussian–Cauchy hybrid variational strategy, and the multiple swarm strategy, thereby improving the global search capability. …”
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Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review by José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, Eduardo Maio, Eduardo Maio, Eduardo Maio, Pedro Afonso, Pedro Afonso, Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, Guilherme F. Machado, Guilherme F. Machado, Ryland Morgans, Tiago M. Barbosa, Tiago M. Barbosa, António M. Monteiro, António M. Monteiro, Pedro Forte, Pedro Forte, Pedro Forte, Ricardo Ferraz, Ricardo Ferraz, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho

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A novel hybrid model based on MPA-VMD, QRMGM and KDE for carbon price prediction by Dabin Zhang, Yufeng Ye, Yongmei Fang, Jing Zhou

“…Thirdly, the MGM was integrated with quantile regression (QR) to predict the conditional quantiles of each subsequence. …”
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SORA: Energy-Efficient Resource Allocation in Open Radio Access Network With Online Learning by Aerman Tuerxun, Akihiro Nakao

“…Our approach is designed to operate with minimal assumptions about the network environment, making it highly adaptable to both stationary and dynamic conditions. By integrating variational inference with Thompson Sampling, the framework efficiently balances exploration and exploitation, allowing dynamic adjustment of MCS and PRB allocations in response to changing network states. …”
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VAE-Based Real-Time Anomaly Detection Approach for Enhanced V2X Communication Security by Yonas Teweldemedhin Gebrezgiher, Sekione Reward Jeremiah, Stefanos Gritzalis, Jong Hyuk Park

“…This paper proposes a real-time anomaly detection framework that integrates the reconstruction capabilities of Variational Autoencoders (VAEs) with the feature extraction power of Convolutional Neural Networks (CNNs). …”
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DOLPHIN advances single-cell transcriptomics beyond gene level by leveraging exon and junction reads by Kailu Song, Yumin Zheng, Bowen Zhao, David H. Eidelman, Jian Tang, Jun Ding

“…We introduce DOLPHIN, a deep learning method that integrates exon-level and junction read data, representing genes as graph structures. …”
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Finding Key Nodes in Complex Networks Through Quantum Deep Reinforcement Learning by Juechan Xiong, Xiao-Long Ren, Linyuan Lü

“…This study proposes a quantum deep reinforcement learning (QDRL) framework that integrates reinforcement learning with a variational quantum graph neural network, effectively identifying distributed influential nodes while preserving the network’s fundamental topological properties. …”
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Effects of Crack on Vibration Characteristics of Mistuned Rotated Blades by Hailong Xu, Zhongsheng Chen, Yongmin Yang, Limin Tao, Xuefeng Chen

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Complying with the EU AI Act: Innovations in explainable and user-centric hand gesture recognition by Sarah Seifi, Tobias Sukianto, Cecilia Carbonelli, Lorenzo Servadei, Robert Wille

“…Leveraging this real-world dataset, we enhance XentricAI’s capabilities by integrating a variational autoencoder module for improved gesture anomaly detection, incorporating user-specific dynamic thresholding. …”
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