Adaptive biases-incorporated latent factorization of tensors for predicting missing data in water quality monitoring networks by Xuke Wu, Xuke Wu, Lan Wang, Lan Wang, Miao Ge, Miao Ge, Jing Jiang, Jing Jiang, Yu Cai, Bing Yang, Bing Yang

Get full text

Utilizing plant-based biogenic volatile organic compounds (bVOCs) to detect aflatoxin in peanut plants, pods, and kernels by Daniel E. Sabo, Justin J. Pitts, Olga Kemenova, Christopher A. Heist, Benjamin Joffe, Xiaojuan (Judy) Song, William M. Hammond

“…Several statistical analysis and machine learning techniques were applied to all the collected GC/MS data. …”
Get full text

Establishing a novel model to assess exercise capacity in chronic heart failure based on stress echocardiography by Huan Cen, Sinan Chen, Shen Feng, Xiankun Chen, Huiying Zhu, Wei Jiang, Han Zhang, Hongmei Liu, Bo Liu, Weihui Lu, Pengtao Sun

Get full text

Assessment of hydrodynamic pressure effect on backhoe-loader movement to wade through the water obstacle by Ye. R. Magdina

“…Transverse (frontal) hydrodynamic resistance, longitudinal (lateral) hydrodynamic pressure and standard reactions on the machine wheels were taken as the main parameters under study.   …”
Get full text

Towards sustainable precision: A review of water jet meso and micromachining by Mohammad Ghasemian Fard, Akash Nag, Jana Petrů, Sergej Hloch

“…It examines the intricate interplay of key process parameters such as abrasive particle size (MESH), nozzle geometry, fluid pressure, and standoff distance, and how these parameters influence machining performance and surface integrity. …”
Get full text

Performance Analysis and Reliability Prediction of Multi‐State Service Systems With Multiple Failure Modes of Unreliable Server: An Engineering Perspective by Shreekant Varshney, Mohit Bajaj, Kapil Kumar Choudhary, Mukesh Pushkarna, Ievgen Zaitsev

“…ABSTRACT The long‐term reliability of a machining system is essential for ensuring the uninterrupted operation of an automated manufacturing process. …”
Get full text

Application of an integrated method to improve the quality of manufacturing parts of electronic warfare devices by A. V. Kryukov

“…The proposed technological solutions based on a synergistic approach provided a balanced improvement in material parameters by eliminating the shortcomings of the original semi-finished product. …”
Get full text

Torque capability enhancement of commercial interior permanent magnet motors using t-shaped notching and merged barrier rotor topology by H.N. Lin, P. Seangwong, N. Fernando, A. Siritaratiwat, P. Khunkitti

Get full text

Research on bearing fault diagnosis based on ISA-VMD and IMSE by Feng Yan

“…Initially, the ISSA algorithm optimizes two critical parameters of the VMD method: the number of modes $$K$$ K and the penalty factor $$\alpha$$ α , to obtain the optimal parameter combination $$[K$$ [ K , $$\alpha$$ α ]. …”
Get full text

Enhancing Fault Diagnosis: A Hybrid Framework Integrating Improved SABO with VMD and Transformer–TELM by Jingzong Yang, Xuefeng Li, Min Mao

“…To address this challenge, this study proposes an intelligent diagnostic method that integrates variational mode decomposition (VMD) optimized by the improved subtraction-average-based optimizer (ISABO) with transformer–twin extreme learning machine (Transformer–TELM) ensemble technology. Firstly, ISABO is employed to finely optimize the initialization parameters of VMD. …”
Get full text

Combined use of long short‐term memory neural network and quantum computation for hierarchical forecasting of locational marginal prices by Xin Huang, Guozhong Liu, Jiajia Huan, Shuxin Luo, Jing Qiu, Feiyan Qin, Yunxia Xu

“…To address the issue of excessively long training times during the design of the LSTM network structure and parameter selection, a QGWO algorithm is proposed and used to optimise four LSTM parameters. …”
Get full text

Evaluation Method of Total Organic Carbon Content in Shale Based on Stacking Algorithm Ensemble Learning by SONG Yanjie, LIU Yingjie, TANG Xiaomin, ZHANG Zhaoqian

“…Machine learning models have improved the prediction accuracy of TOC to a certain extent, but the results are unstable. …”
Get full text

Real-time prediction of the rate of penetration via computational intelligence: a comparative study on complex lithology in Southwest Iran by Mohammad Najafi, Yousef Shiri

“…Abstract The rate of penetration (ROP) is a critical parameter for optimizing oil well drilling and the overall cost of drilling operations. …”
Get full text

Artificial Intelligence Dystocia Algorithm (AIDA) as a Decision Support System in Transverse Fetal Head Position by Antonio Malvasi, Lorenzo E. Malgieri, Tommaso Difonzo, Reuven Achiron, Andrea Tinelli, Giorgio Maria Baldini, Lorenzo Vasciaveo, Renata Beck, Ilenia Mappa, Giuseppe Rizzo

“…The predictive capabilities of three machine learning algorithms (Support Vector Machine, Random Forest, and Multilayer Perceptron) were assessed, and delivery outcomes were analyzed. …”
Get full text

Federated Learning for Surface Roughness by Kai-Lun Cheng, Yu-Hung Ting, Wen-Ren Jong, Shia-Chung Chen, Zhe-Wei Zhou

“…This study proposes a federated learning-based real-time surface roughness prediction framework for WEDM to address issues of empirical parameter tuning and data privacy. By sharing only the model parameters, cross-machine training was enabled without exposing raw data. …”
Get full text

Random forest regressor for predicting sensory texture of emotional designed packaging films by Yong Ju Lee, Min Jung Joo, Ha Kyoung Yu, Tai-Ju Lee, Hyoung Jin Kim

“…This study demonstrates a robust framework for integrating machine learning in packaging design to optimize sensory appeal.…”
Get full text

Rapid detection method for pork freshness using fusion spectroscopy and improved BAS-LSSVM by WANG Yao, REN Xiaozhen

“…ObjectiveTo realize accurate, rapid, and non-destructive testing of meat freshness.MethodsExtracting spectral feature information based on a spectral acquisition system, proposed a fast non-destructive detection method for meat freshness (TVB-N) by combining an improved beetle whisker search algorithm with least squares support vector machine. By combining SG smoothing filtering and standard normal variables for data preprocessing, combining window competitive adaptive reweighted sampling and iterative continuous projection for feature selection, regularization parameters and kernel parameters of Least-Square Support Vector Machine were optimized by the Improved Beetle Antennae Search Algorithm, a fast non-destructive detection method for meat freshness (TVB-N) was completed. …”
Get full text

Assessment of the effect of the process-induced porosity defects on the fatigue properties of wire arc additive manufactured Al–Si–Mg alloy by Teng Zhan, Ke Xu, Zhipeng Fan, Hanlin Xiang, Congchang Xu, Tianjiao Mei, Yuanyuan Wei, Wentao Chen, Luoxing Li

“…The importance of four parameters in limiting fatigue life is ranked in the above order.…”
Get full text

Prediction of Thyroid Classes Using Feature Selection of AEHOA Based CNN Model for Healthy Lifestyle by Rachappa Jopate, Piyush Kumar Pareek, DivyaJyothi M. G, Ariam Saleh Zuwayid Juma Al Hasani

“…Correct classification and machine learning substantially improve thyroid disease diagnosis. …”
Get full text

On the interpretability of the SVM model for predicting infant mortality in Bangladesh by Md Abu Sayeed, Azizur Rahman, Atikur Rahman, Rumana Rois

“…Abstract Background Although machine learning (ML) models are well-liked for their outperformance in prediction, greatly avoided due to the lack of intuition and explanation of their predictions. …”
Get full text