A dynamic prediction model of landslide displacement based on VMD–SSO–LSTM approach by Haiying Wang, Yang Ao, Chenguang Wang, Yingzhi Zhang, Xiaofeng Zhang

“…The proposed method combines Variational Mode Decomposition (VMD) with Sparrow Search Optimization (SSO) and Long Short-Term Memory (LSTM) techniques to formulate a comprehensive VMD–SSO–LSTM model. …”
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Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model by Haixiang Zang, Lei Fan, Mian Guo, Zhinong Wei, Guoqiang Sun, Li Zhang

“…Ultimately, our forecasting model is more suitable for engineering applications and other forecasting methods for new energy.…”
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The use of the surface location approach in the modeling of periodically nonhomogeneous slender visco-elastic beams by Dorota Kula

“…Revisiting by Jarosław Jędrysiak, published in scientific journal “Materials” in 2020, but it differs in the way of the use of tolerance modeling in the beam theory. The mathematical tool of considerations is a special choice of the micro-macro decomposition of the beam deflection. …”
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Observation of Electroplating in a Lithium-Metal Battery Model Using Magnetic Resonance Microscopy by Rok Peklar, Urša Mikac, Igor Serša

“…Accurate imaging methods are important for understanding electrodeposition phenomena in metal batteries. …”
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Twin Support Vector Regression Model Based on Heteroscedastic Gaussian Noise and Its Application by Shiguang Zhang, Ge Feng, Feng Yuan, Shuangle Guo

“…In this paper, the characteristics of heteroscedasticity Gaussian noise are introduced into the model TSVR, and the twin support vector regression model based on heteroscedasticity Gaussian noise (TSVR-HGN) is constructed. …”
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The role of hybrid models in financial decision-making: Forecasting stock prices with advanced algorithms by Xiaoyi Zhu

“…In comparison to other methods, the proposed model demonstrated superior performance on the S&P 500, with an R2 of 0.99 and low error metrics. …”
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Evaluation of in-vessel co-composting of yard waste and development of kinetic models for co-composting by K. M. Sangamithirai, J. Jayapriya, J. Hema, Ravi Manoj

“…In addition to that, kinetic models were developed to predict the decomposition rate constant of the process.…”
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Cooperative Hybrid Modelling and Dimensionality Reduction for a Failure Monitoring Application in Industrial Systems by Morgane Suhas, Emmanuelle Abisset-Chavanne, Pierre-André Rey

“…In conclusion, the CHMC model offers a generalisable method with significant advantages in fault detection, model adaptation, and predictive maintenance performance across varying usage profiles and on unseen operational scenarios.…”
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LoRA fine-tuning of Llama3 large model for intelligent fishery field by Yao Song, Chunli Lv, Kun Zhu, Xiaobin Qiu

“…This article introduces the basic principles of the Llama3 model and LoRA fine-tuning technology, and elaborates on the specific implementation method of applying LoRA technology to the Llama3 model. …”
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Electrochemical approach for monitoring the catalytic action of immobilized catalase by Peshkov Angel, Shukri Merin, Pimpilova Mariya, Iliev Ilia, Dimcheva Nina

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An Interpretable Method for Asphalt Pavement Skid Resistance Performance Evaluation Under Sand-Accumulated Conditions Based on Multi-Scale Fractals by Yuhan Weng, Zhaoyun Sun, Huiying Liu, Yingbin Gu

“…The SHapley Additive exPlanations (SHAP) method is used to analyze the optimal model’s interpretability. …”
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ZenLDA: Large-Scale Topic Model Training on Distributed Data-Parallel Platform by Bo Zhao, Hucheng Zhou, Guoqiang Li, Yihua Huang

“…On top of MCCB, the ZenLDA formula decomposition achieved the fastest speed among other well-known inference methods. …”
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Diagnosis Method for High-Speed Train Axle Box Bearing Slight Faults Based on Improved SAE and Temperature-Vibration Fusion by XU Xiao, SONG Dongli, WANG Zifan

“…［Method］ First, an AE (auto encoder) driven bearing temperature feature extraction method is designed to obtain the abnormal bearing temperature features, and EMD (empirical modal decomposition) method is used to process the vibration signal，so as to obtain the statistical features of the effective vibration IMF (intrinsic modal function). …”
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The VMD-Informer-BiLSTM-EAA Hybrid Model for Predicting Zenith Tropospheric Delay by Zhengdao Yuan, Xu Lin, Yashi Xu, Ruiting Dai, Cong Yang, Lunwei Zhao, Yakun Han

“…Additionally, it takes into account the non-stationarity of the ZTD sequence. The model employs the Variational Mode Decomposition (VMD) method to address the non-stationarity of ZTD. …”
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Air Quality and Healthy Ageing: Predictive Modeling of Pollutants Using CNN Quantum-LSTM by Fareena Naz, Muhammad Fahim, Adnan Ahmad Cheema, Bradley D. E. Mcniven, Tuan-Vu Cao, Ruth Hunter, Trung Q. Duong

“…In this work, we proposed a hybrid model referred as AirVCQnet, which combines the variational mode decomposition (VMD) method with a convolutional neural network (CNN) and a quantum long short-term memory (QLSTM) network for the prediction of air pollutants. …”
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Modeling soil respiration in summer maize cropland based on hyperspectral imagery and machine learning by Fanchao Zeng, Fanchao Zeng, Jinwei Sun, Huihui Zhang, Lizhen Yang, Xiaoxue Zhao, Jing Zhao, Xiaodong Bo, Yuxin Cao, Fuqi Yao, Fenghui Yuan, Fenghui Yuan

“…However, it remains uncertain whether hyperspectral remote sensing can provide an accurate and efficient method for estimating SR rate in croplands, particularly across different maize growth stages of under varying drought conditions.MethodsIn the study, we investigated the potential of combining hyperspectral remote sensing data with machine learning model (ML) to quantify SR rate in croplands. …”
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An Inverse Modeling Multi-Objective Optimization Technique Based on Incremental Learning and Fuzzy Clustering by Gadallah Mohamed Abd Elaziz, Yasmine Abouelseoud, Sara H. Kamel

“…This paper aims to develop an inverse modeling MOEA based on decomposition that employs an incremental learning-based support vector regression (SVR) model, as an alternative to the Gaussian process model, in order to improve the quality of obtained solutions and speed up convergence of the algorithm. …”
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Educational resources recommendation algorithm based on GMF-MLP-NeuMF prediction model by Rui Wang, Qiusheng Cui, Yezhi Xiao, Jinfeng Du, Ruicheng Yue

“…Traditional collaborative filtering methods often struggle with precision in modeling user-resource interactions, particularly in dynamic educational environments. …”
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GPTArm: An Autonomous Task Planning Manipulator Grasping System Based on Vision–Language Models by Jiaqi Zhang, Zinan Wang, Jiaxin Lai, Hongfei Wang

“…The integration of vision–language models (VLMs) with robotic systems represents a transformative advancement in autonomous task planning and execution. …”
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Construction of a health literacy prediction model for diabetic patients: A multicenter study by Zepeng Wang, Junyi Shi, Fangyuan Jiang, Kui Jiang, Yalan Chen

“…Calibration curves, decomposition plots, and partial dependence plots were drawn to evaluate and interpret the models. …”
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