The Impact of the Natural Grass-Growing Model on the Development of Korla Fragrant Pear Fruit, as Well as Its Influence on Post-Harvest Sugar Metabolism and the Expression of Key E... by Mingyang Yu, Lanfei Wang, Yan Chen, Weifan Fan, Hao Wang, Kailu Guo, Shutian Tao, Xin Gong, Jianping Bao

“…Sugar components, enzyme activities, and gene expression levels in the pulp and peel were comprehensively analyzed during fruit development and storage. A classification model was constructed using machine learning algorithms (RF, KNN, SVM), and particle swarm optimization (PSO) was employed to identify key factors. …”
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Establishment and validation of a dynamic nomogram to predict short-term prognosis and benefit of human immunoglobulin therapy in patients with novel bunyavirus sepsis in a populat... by Kai Yang, Bin Quan, Lingyan Xiao, Jianghua Yang, Dongyang Shi, Yongfu Liu, Jun Chen, Daguang Cui, Ying Zhang, Jianshe Xu, Qi Yuan, Yishan Zheng

“…The optimal model, incorporating consciousness, LDH, AST, and age, was used to construct a dynamic nomogram. …”
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Aerodynamic Parameter Identification of Projectile Based on Improved Extreme Learning Machine and Ensemble Learning Theory by Tianyi Wang, Wenjun Yi, Youran Xia

“…To obtain the aerodynamic parameters of the projectile accurately, an aerodynamic parameter identification model based on ensemble learning theory and ELM optimized by improved particle swarm optimization is proposed. …”
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Machine learning approach for prediction of safe mud window based on geochemical drilling log data by Hongchen Cai, Yunliang Yu, Yingchun Liu, Xiangwei Gao

“…Traditional geomechanical methods for SMW determination face challenges in handling complex, nonlinear relationships within drilling datasets.PurposeThis study aims to develop robust machine learning (ML) models to predict two key SMW parameters—Mud Pressure below shear failure (MWsf) and tensile failure (MWtf)—using geochemical drilling log data from Middle Eastern carbonate reservoirs.MethodsHybrid ML models combining Least Squares Support Vector Machine (LSSVM) and Multilayer Perceptron (MLP) with optimization algorithms (Gray Wolf Optimization, GWO; Grasshopper Optimization Algorithm, GOA) were trained on 2,820 data points from three wells. …”
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APPLICATION OF SEMI SUPERVISED LAPLACE SCORE IN ROLLING BEARING FAULT DIAGNOSIS (MT) by LIANG Chuang, CHEN ChangZheng, LIU Ye, JIA XinYing

“…At the same time, particle swarm optimization-based support vector machine（PSO-SVM） algorithm is used for fault classification. …”
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Machine Learning in the Design and Performance Prediction of Organic Framework Membranes: Methodologies, Applications, and Industrial Prospects by Tong Wu, Jiawei Zhang, Qinghao Yan, Jingxiang Wang, Hao Yang

“…Methodologically, ML workflows—spanning data construction, feature engineering, and model optimization—accelerate candidate screening, inverse design, and mechanistic interpretation, as demonstrated in gas separations and nascent liquid-phase applications. …”
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Back analysis of geomechanical parameters based on a data augmentation algorithm and machine learning technique by Hui Li, Weizhong Chen, Xianjun Tan

“…Subsequently, we harness the power of optimized particle swarm optimization (OPSO) integrated with support vector machine (SVM) to mine the intricate nonlinear relationships between input and output variables. …”
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Machine learning of automatic hierarchical multi-label classification method for identifying metal failure mechanisms by Ruitong Han, Chang-Bo Liu, Wanting Sun, Shuai Yu, Haoran Zheng, Lin Deng

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Ensemble machine learning algorithm for cost-effective and timely detection of diabetes in Maiduguri, Borno State by Emmanuel Gbenga Dada, Aishatu Ibrahim Birma, Abdulkarim Abbas Gora

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Neural Machine Translation in Electrical Engineering With Cross-Layer Information Fusion and Multiple Positional Mapping by Zhenyu Zhang, Yuan Chen, Juwei Zhang

“…Such texts are usually dense in terms, complex in sentence structure, deeply nested in structure, and have low resources, which poses significant challenges to existing neural machine translation models. Aiming at the problem of attenuation of inter-layer semantic information and position information in text encoding of Transformer model in the field of electrical engineering, an optimization method based on cross-layer information fusion and multiple position mapping is proposed. …”
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Time to failure prediction for MLCCs: A machine learning approach based on leakage current data by Tianyu Jiang, Jincheng Qin, Faqiang Zhang, Mingcao Li, Xiaolian Yan, Mingsheng Ma, Yongxiang Li, Zhifu Liu

“…This study addresses this gap by developing a machine learning model to predict the TTF of individual MLCCs. …”
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DESIGN AND STUDY OF DRIVE SWIVEL JOINTS FOR HYDRAULIC MANIPULATION SYSTEMS OF MOBILE TRANSPORT-TECHNOLOGICAL MACHINES by Lagerev A.V., Lagerev I.A.

“…Developed a mathematical optimization model. The model is based on the minimization of the mass of the drive swivel joints when you complete the necessary design, installation, operating and strength constraints. …”
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Integrating machine learning and symbolic regression for predicting damage initiation in hybrid FRP bolted connections by Sherif Samy Sorour, Chahinaz Abdelrahman Saleh, Mostafa Shazly

“…Abstract The increasing adoption of machine learning (ML) in fiber-reinforced polymer (FRP) composite design has led to a reliance on black-box models, which achieve high predictive accuracy but lack interpretability. …”
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Estimating Maize Leaf Water Content Using Machine Learning with Diverse Multispectral Image Features by Yuchen Wang, Jianliang Wang, Jiayue Li, Jiacheng Wang, Hanzeyu Xu, Tao Liu, Juan Wang

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QDLTrans: Enhancing English Neural Machine Translation With Quantized Attention Block and Tunable Dual Learning by Xing Liu

“…Through a two-stage optimization process, we mitigate knowledge interference during fine-tuning using DoRA (Weight-Decomposed Low-Rank Adaptation), further enhancing model performance. …”
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Dynamic Analysis and Scale Optimization of Prefabricated Building Wall Panel Installation by Jiang Mingyang, Zhang Lin, Liu Hongbin, Sima Mingyang, Yu Ningtao

“…Based on Creo software, a virtual prototype of the prefabricated building wall panel installation machine before and after optimization is established, and dynamic simulation analysis is performed to verify the correctness of the scale optimization model. …”
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Crystal’s Self-Alignment for High Power Laser Facility Based on Machine Learning by Yaohan Kang, Daizhong Liu, Xiuqing Jiang, Lei Gong, Xingqiang Lu, Mingying Sun

“…M-LOOP employs Bayesian optimization based on Gaussian process probabilistic agent model. …”
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Application of machine learning for real-time water quality monitoring in developing countries: A review by Samson Otieno Ooko, Laura Cheptegei, Simon M. Karume

“…Unlike previous reviews, this study explores model optimization techniques, data limitations, and challenges in scaling ML-based solutions. …”
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Integrating Dimensional Analysis and Machine Learning for Predictive Maintenance of Francis Turbines in Sediment-Laden Flow by Álvaro Ospina, Ever Herrera Ríos, Jaime Jaramillo, Camilo A. Franco, Esteban A. Taborda, Farid B. Cortes

“…This understanding, in turn, informs the selection and interpretation of features for machine learning (ML) models aimed at the predictive maintenance of the target variable and important features for the next stage. …”
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Interpretable Prediction of a Decentralized Smart Grid Based on Machine Learning and Explainable Artificial Intelligence by Ahmet Cifci

“…This study addresses this challenge by leveraging machine learning (ML) models and explainable artificial intelligence (XAI) techniques to predict the stability of a decentralized smart grid. …”
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