A Multi-Strategy Optimized Framework for Health Status Assessment of Air Compressors by Dali Hou, Xiaoran Wang

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A general cubic spline smooth semi-supervised support vector machine by ZHANG Xiao-dan, MA Jing-gai

“…This article is focused on the non-smooth problem of the semi-supervised support vector machine optimization model. A smooth semi-supervised support vector machine model was established. …”
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Optimization of the Screw Conveyor Device Based on a GA-BP Neural Network by Qiang Guo, Yunpeng Zhuang, Houzhuo Xu, Wei Li, Haitao Li, Zhidong Wu

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Tooling systems with integrated sensors enabling data based process optimization by Friedrich Bleicher, Christoph Ramsauer, Martin Leonhartsberger, Matthias Lamprecht, Philipp Stadler, Dominik Strasser, Clemens Wiedermann

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Optimizing hypertension prediction using ensemble learning approaches. by Isteaq Kabir Sifat, Md Kaderi Kibria

“…This research contributes to ongoing efforts to optimize HTN prediction models, ultimately supporting early intervention and personalized healthcare management.…”
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Application analysis of radiomics models based on high-resolution T2-weighted MR images for evaluating the effectiveness of neoadjuvant chemoradiotherapy in locally advanced rectal... by Liu Minglu, Shen Fu, Wang Hao, Chen Qi, Lu Jianping

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Biomimetic Origami: Planar Single-Vertex Multi-Crease Mechanism Design and Optimization by Yihang Wang, Yongsheng Zhao, Bo Han, Jinming Dong, Meng Han, Jiantao Yao

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Screw Conveyor Rotor Multi-objective Optimization Design by ZHANG Yuan, JIANG Xiao-han, FAN Hua-ping, LI Xi-han

“…The optimized rotor deformation can be reduced to 65% of the original model and the frequency is increased by 13%. …”
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Fast autoscaling algorithm for cost optimization of container clusters by José María López, Joaquín Entrialgo, Manuel García, Javier García, José Luis Díaz, Rubén Usamentiaga

“…The main motivation for the development of FCMA has been to significantly reduce the solving time of the resource allocation problem compared to a previous state-of-the-art optimal Integer Linear Programming (ILP) model. In addition, FCMA addresses secondary objectives to improve fault tolerance and reduce container and virtual machine recycling costs, load-balancing overloads and container interference. …”
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Schur Complement Optimized Iterative EKF for Visual–Inertial Odometry in Autonomous Vehicles by Guo Ma, Cong Li, Hui Jing, Bing Kuang, Ming Li, Xiang Wang, Guangyu Jia

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Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone by Yuyu Sun, Yuchen Zhang, Zhiguo Zhao

“…Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models. …”
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An integrated approach of feature selection and machine learning for early detection of breast cancer by Jing Zhu, Zhenhang Zhao, Bangzheng Yin, Canpeng Wu, Chan Yin, Rong Chen, Youde Ding

“…Optimizing hyperparameters of five models using the Particle Swarm Optimization (PSO) algorithm. …”
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Harnessing Machine Learning for Predictive Analysis of Crop Resistance to Extreme Weather Conditions by Pan Susovan Kumar, Shivaj Ghorpade Bipin

“…Weather and crop responses are captured and also forecasted with better accuracy using Long Short Term Memory networks and Sequence to Sequence models. To fine tune model hyperparameters in a way of optimizing performance and computational efficiency, Bayesian Optimization is used. …”
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A Fourth-Order Fuzzy Support Vector Machine Based on Class Center by Yongqiang Zhou, Zhenggang Song

“…In addition, the specific expression of the model is derived by solving the convex optimization problem. …”
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Enhancing structural health monitoring with machine learning for accurate prediction of retrofitting effects by A. Presno Vélez, M. Z. Fernández Muñiz, J. L. Fernández Martínez

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Classification Based on Brain Storm Optimization With Feature Selection by Yu Xue, Yan Zhao, Adam Slowik

“…Classification is one of the most classic problems in machine learning. Due to the global optimization ability, evolutionary computation (EC) techniques have been successfully applied to solve many problems and the evolutionary classification model is one of the methods used to solve classification problems. …”
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KINEMATIC AND DYNAMIC ANALYSIS OF MARKING MECHANISM OF ONE STEEL PLATE MARKING MACHINE by FU Min, LIN LiFeng

“…The marking mechanism,as an important part of one steel plate marking machine that before heat treatment,its dynamic characteristic could influence marking effect.First,estiblished 3D model of marking mechanism by Pro/E,using the condition of marking typical character "N " as example,kinematics analysis have been done,obtain the law of speed and acceleration varies with time when marking character;on the basis of it,build the finite element model of marking mechanism according to actual condition and transient dynamics analysis has been completed based on Ansys Workbench,solved the curve of maximium stress and deformation varies with time,the result shows that the intensity and stiffness of marking mechanism could satisfy the requirement,and provide theory foundation for the structure design and optimization.…”
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Online Large-Scale Taxi Assignment: Optimization and Learning by Omar Rifki, Thierry Garaix

“…Our optimization model is based on the Bertsimas et al. (2019) re-optimization approach. …”
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Global Research Trends in Biomimetic Lattice Structures for Energy Absorption and Deformation: A Bibliometric Analysis (2020–2025) by Sunny Narayan, Brahim Menacer, Muhammad Usman Kaisan, Joseph Samuel, Moaz Al-Lehaibi, Faisal O. Mahroogi, Víctor Tuninetti

“…Key research focuses include additive manufacturing, finite element modeling, machine learning-based design optimization, and the performance evaluation of bioinspired geometries. …”
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Machine learning analysis of rivaroxaban solubility in mixed solvents for application in pharmaceutical crystallization by Mohammed Alqarni, Ali Alqarni

“…Abstract This study investigates the use of machine learning models to predict solubility of rivaroxaban in binary solvents based on temperature (T), mass fraction (w), and solvent type. …”
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