Effective feature selection based HOBS pruned- ELM model for tomato plant leaf disease classification. by M Amudha, K Brindha

“…The classification module integrates a Hessian-based Optimal Brain Surgeon (HOBS) approach with a pruned Extreme Learning Machine (ELM), optimizing network parameters while reducing computational complexity. …”
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The Role of Artificial Intelligence in Boosting Cybersecurity and Trusted Embedded Systems Performance: A Systematic Review on Current and Future Trends by Ahmed Oun, Kaden Wince, Xiangyi Cheng

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The Role of Pharmacometrics in Advancing the Therapies for Autoimmune Diseases by Artur Świerczek, Dominika Batko, Elżbieta Wyska

“…<b>Methods</b>: This review synthesizes research from the past two decades on pharmacometric methodologies, including Physiologically Based Pharmacokinetic (PBPK) modeling, Pharmacokinetic/Pharmacodynamic (PK/PD) modeling, disease progression (DisP) modeling, population modeling, model-based meta-analysis (MBMA), and Quantitative Systems Pharmacology (QSP). …”
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Enhanced brain tumor diagnosis using combined deep learning models and weight selection technique by Karim Gasmi, Najib Ben Aoun, Najib Ben Aoun, Khalaf Alsalem, Ibtihel Ben Ltaifa, Ibrahim Alrashdi, Lassaad Ben Ammar, Manel Mrabet, Abdulaziz Shehab

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End-to-End Architecture for Real-Time IoT Analytics and Predictive Maintenance Using Stream Processing and ML Pipelines by Ouiam Khattach, Omar Moussaoui, Mohammed Hassine

“…The architecture incorporates continuous monitoring and optimization components to track system performance and model accuracy, feeding insights to users via a dedicated Application Programming Interface (API). …”
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Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm by El-Sayed M. El-Kenawy, Nima Khodadadi, Marwa M. Eid, Ehsaneh Khodadadi, Ehsan Khodadadi, Doaa Sami Khafaga, Amel Ali Alhussan, Abdelhameed Ibrahim, Mohamed Saber

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Gradient Boosting Feature Selection for Integrated Fault Diagnosis in Series-Compensated Transmission Lines by Rab Nawaz, Abdul Wadood, Khawaja Khalid Mehmood, Syed Basit Ali Bukhari, Hani Albalawi, Aadel Mohammed Alatwi, Muhammad Sajid

“…The methodology is implemented using four ensemble classifiers: Adaptive Boosting (AB), Light Gradient Boosting Machine (LGBM), Random Forest (RF), and Extreme Gradient Boosting (XGB), and is rigorously evaluated on various standard models of differing complexity and system configurations under dynamic conditions. …”
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Analysis of Cogging Torque Ripple Based on Multiple Square-Wave Radial Superposition MMF for Wound-Field Synchronous Motors by Tingting Hou, Jiakuan Xia, Jin Chen, Meijun Qi

“…Based on the finite element model, the cogging torque ripple, key electromagnetic performance, and vibration spectrum of the machine before and after optimization are compared. …”
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Prediction of Key Quality Parameters in Hot Air-Dried Jujubes Based on Hyperspectral Imaging by Quancheng Liu, Chunzhan Yu, Yuxuan Ma, Hongwei Zhang, Lei Yan, Shuxiang Fan

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Cyclic peptide membrane permeability prediction using deep learning model based on molecular attention transformer by Dawei Jiang, Zixi Chen, Zixi Chen, Hongli Du

“…Its performance outperforms traditional machine learning methods and graph-based neural network models. …”
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Artificial intelligence in predicting pathogenic microorganisms’ antimicrobial resistance: challenges, progress, and prospects by Yan Li, Xiaoyan Cui, Xiaoyan Yang, Guangqia Liu, Juan Zhang

“…Subsequently, we highlight the main AI and ML models used in resistance prediction, including but not limited to Support Vector Machines, Random Forests, and Deep Learning networks. …”
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Semi-Supervised Anomaly Detection for the Identification of Damages in an Aerospace Sandwich Structure Based on Synthetically Generated Strain Data by Florian Forsthuber, Christoph Kralovec, Martin Schagerl

“…The structural health monitoring (SHM) of safety relevant composite components is becoming increasingly relevant as it enables in-service diagnosis and data acquisition capabilities, contributing to the optimization and efficient operation of the overall system and ultimately saving costs and resources. …”
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A novel interval prediction method in wind speed based on deep learning and combination prediction by XueJun Chen, Tao Han, Peng Cheng, Xuanfang Da

“…Finally, the selected models are combined by a multi-objective optimizer to obtain the final prediction. …”
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Research on the spatial layout of the elderly care industry based on explainable machine learning: A case study of Hangzhou(基于可解释性机器学习的养老产业空间布局研究)... by 曾笑奇(ZENG Xiaoqi), 赵秋皓(ZHAO Qiuhao), 冯友建(FENG Youjian)

“…Utilizing data from the Seventh National Population Census and POI data, we compare the prediction accuracy of three machine learning models—decision tree (DT), random forest (RF), and extreme gradient boosting tree (XGBoost). …”
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ML-Based Control Strategy for PHEV Under Predictive Vehicle Usage Behaviour by Aleksandr Doikin, Aleksandr Korsunovs, Felician Campean, Oscar García-Afonso, Enrico Agostinelli

“…This paper introduces a novel strategy for an intelligent plug-in hybrid electric vehicle (PHEV) energy optimization strategy based on machine learning (ML) prediction of the upcoming journey, without recourse to navigation or other external data, which underpins many of the existing approaches. …”
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Brain Tumour Detection Using VGG-Based Feature Extraction With Modified DarkNet-53 Model by S. Trisheela, Roshan Fernandes, Anisha P. Rodrigues, S. Supreeth, B. J. Ambika, Piyush Kumar Pareek, Rakesh Kumar Godi, G. Shruthi

“…We propose a modified DarkNet-53 architecture, optimized with invasive weed optimization (IWO), to extract critical features from preprocessed MRI images. …”
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Study on the Interactions Process of Coupled Model of Furrow Opener–Soil–Pot Seedling Based on Discrete Approach by Bin Jiang, Jinping Cai, Xiongfei Chen, Junan Liu, Liping Xiao, Jinlong Lin, Yuqiang Chen

“…The coupled model provides technical support for the design and parameter optimization of rice planting equipment.…”
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Quantitative analysis of gait parameters in Parkinson’s disease and the clinical significance by Wenchao Yin, Hong Gao, Beichen Liang, Ruichen Liu, Yue Liu, Chenxin Shen, Xiaohui Niu, Cui Wang

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Characterization of braided river reservoir architecture based on seismic attribute stacking ensemble learning: A case study of the C-2 oilfield in the Bohai Bay Basin by ZHANG Zhang, MENG Peng, YANG Wei, ZHANG Xiaolong, HUANG Qi, WANG Haoran

“…This approach significantly improved prediction accuracy compared to a single machine learning model. By integrating multi-dimensional information such as geology, geophysics, and reservoir dynamics, iterative optimization was conducted to further reduce the uncertainty in subsurface reservoir prediction and structural understanding. …”
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A Distributional Regression Network With Data Transformation for Calibrating Rainfall Forecasts by Zeqing Huang, Andrew Schepen, James C. Bennett, David E. Robertson, Tongtiegang Zhao, Eun‐Soon Im, Quan J. Wang

“…Abstract Machine learning methods provide a promising approach for exploiting relationships between raw forecasts and observations for forecast calibration. …”
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