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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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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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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Twin Support Vector Regression Model Based on Heteroscedastic Gaussian Noise and Its Application by Shiguang Zhang, Ge Feng, Feng Yuan, Shuangle Guo

“…The Lagrange multiplier method is used to solve the problem, and the optimization algorithm is used to find the global optimization. …”
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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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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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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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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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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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Marine motor fault diagnosis based on CEEMDAN and BRECAN under strong noise conditions by Renjie ZHU, Enzhe SONG, Chong YAO, Yun KE

“…ObjectiveThe background noise in the engine room during actual ship navigation leads to the poor accuracy in fault diagnosis methods. To address this issue, this paper proposes a ship motor fault diagnosis method based on complementary ensemble empirical mode decomposition (EEMD) with adaptive noise (CEEMDAN) and a Bayesian residual efficient channel attention network (BRECAN). …”
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GPPK4PCM: pest classification model integrating growth period prior knowledge by Jianhua Zheng, Junde Lu, Yusha Fu, Ruolin Zhao, Jinfang Liu, Zhaoxi Luo, Zhijie Luo

“…The model is composed of three sub-modules where: i) A deep learning network first identifies the growth periods of pests, and this prior knowledge is then used to guide the text encoder of the CLIP pre-trained model in generating period-specific textual features. ii) A parallel deep learning network extracts visual features from pest images. iii) An efficient low-rank multimodal fusion module integrates textual and visual features through parameter-optimized tensor decomposition, significantly improving classification accuracy across pest developmental phases. …”
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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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Convolutional Neural Network Compression via Dynamic Parameter Rank Pruning by Manish Sharma, Jamison Heard, Eli Saber, Panagiotis Markopoulos

“…Our experiments demonstrate that the proposed method can reduce model parameters by up to 50% and improve classification accuracy by up to 2% over baseline models, making CNNs more feasible for practical applications.…”
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A Fault Diagnosis Model Based on LCD-SVD-ANN-MIV and VPMCD for Rotating Machinery by Songrong Luo, Junsheng Cheng, Kexiang Wei

“…However, traditional class discrimination methods such as SVM and ANN fail to capitalize the interactions among the feature variables. …”
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Discretization-independent surrogate modeling of physical fields around variable geometries using coordinate-based networks by James Duvall, Karthik Duraisamy

“…The incorporation of random Fourier features greatly enhanced prediction and generalization accuracy for both approaches. DVH models have more trainable weights than a similar DV-MLP model, but an efficient batch-by-case training method allows DVH to be trained in a similar amount of time as DV-MLP. …”
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A Hybrid Fault Diagnosis Model for Rolling Bearing With Optimized VMD and Fuzzy Dispersion Entropy by Xin Xia, Xiaolu Wang, Weilin Chen

“…Firstly, a parameter optimization method using the sparrow search algorithm (SSA) was applied to VMD to improve the decomposition ability. …”
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