Extreme gradient boosting algorithm based urban daily traffic index prediction model: a case study of Beijing, China by Jiancheng Weng, Kai Feng, Yu Fu, Jingjing Wang, Lizeng Mao

“…Based on long-term historical TPI data, this research proposed a daily dimensional road network TPI prediction model by using an extreme gradient boosting algorithm (XGBoost). …”
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Parameter extraction of PV models under varying meteorological conditions using a modified electric eel foraging optimization algorithm by Hadeer Khalifa, Mohamed Ebeed, Gaber Magdy, Sherif A. Khaleel, Mohamed I. Shehata, Moataz M. Salah, Francisco Jurado, Hossam Hassan Ali

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Construction of a risk prediction model for postoperative deep vein thrombosis in colorectal cancer patients based on machine learning algorithms by Xin Liu, Xingming Shu, Yejiang Zhou, Yifan Jiang

“…The XGBoost model demonstrated strong potential for improving early detection and treatment in clinical settings.…”
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An application of Arctic puffin optimization algorithm of a production model for selling price and green level dependent demand with interval uncertainty by Hachen Ali, Md. Al-Amin Khan, Ali Akbar Shaikh, Adel Fahad Alrasheedi, Seyedali Mirjalili

“…To assess the accuracy and reliability of the proposed model, the Arctic Puffin Optimization (APO) algorithm is employed to analyze and solve a specific numerical illustration. …”
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Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study by Chuang Li, Youbei Lin, Xuyang Xiao, Xinru Guo, Jinrui Fei, Yanyan Lu, Junling Zhao, Lan Zhang

“…This study demonstrates that machine learning models—particularly the RF algorithm—hold substantial promise for predicting kinesiophobia in postoperative lung cancer patients. …”
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Intelligent algorithm-based model for predicting mass transfer performance in CO2 absorption within a rotating packed bed by Wei Zhang, Hao Chen, Ke Huang, Xing Shu, Cheng Fu, Bin Huang

“…To address these challenges, this study introduces three advanced intelligent models aimed at improving the prediction of the mass transfer coefficient. …”
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Improved Sliding Mode Active Disturbance Rejection Control for Single-inductance Dual-output Buck Converter by HUANG Jinfeng, ZHOU Jie

“…For such strongly coupled nonlinear systems, advanced nonlinear control techniques can substantially improve both dynamic response and control precision.MethodsActive disturbance rejection control (ADRC) has emerged as a promising strategy owing to its strong disturbance rejection capability and independence from precise system modeling. …”
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A super-resolution algorithm to fuse orthogonal CT volumes using OrthoFusion by Rebecca E. Abbott, Alain Nishimwe, Hadi Wiputra, Ryan E. Breighner, Arin M. Ellingson

“…Results demonstrate that OrthoFusion significantly reduced segmentation time, while improving structural similarity of bone images and relative accuracy of derived bone model geometries. …”
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The Impact of Different Parallel Strategies on the Performance of Kriging-Based Efficient Global Optimization Algorithms by Hang Fu, Qingyu Wang, Takuji Nakashima, Rahul Bale, Makoto Tsubokura

“…A parallel efficient global optimization (EGO) algorithm with a pseudo expected improvement (PEI) multi-point sampling criterion, proposed in recent years, is developed to adapt the capabilities of modern parallel computing power. …”
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Improvement of metaphor understanding via a cognitive linguistic model based on hierarchical classification and artificial intelligence SVM by Dongmei Zhu

“…It proposes a metaphor recognition algorithm that combines a Convolutional Neural Network (CNN) with a Support Vector Machine (SVM). …”
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Extraction and Analysis of Influencing Factors of Scientific and Technological Ability Improvement of University Teachers Based on Deep Learning Model by Aiqin Wang, Wei Yan

“…In order to improve the development and construction level of colleges and universities and help teachers improve their scientific and technological abilities, a model based on deep learning model for the extraction and analysis of factors affecting the improvement of college teachers’ scientific and technological abilities was proposed. …”
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Day-ahead photovoltaic power generation forecasting with the HWGC-WPD-LSTM hybrid model assisted by wavelet packet decomposition and improved similar day method by Ruxue Bai, Jinsong Li, Jinsong Liu, Yuetao Shi, Suoying He, Wei Wei

“…This study introduces an innovative hybrid model (HWGC-WPD-LSTM) that integrates an improved similar day algorithm (WGC: weighted grey correlation analysis and cosine similarity), Wavelet Packet Decomposition (WPD), and Long Short-Term Memory neural network (LSTM) for predicting day-ahead power output. …”
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Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). …”
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Low-Power Portable System for Power Grid Foreign Object Detection Based on the Lightweight Model of Improved YOLOv7 by Yonghuan He, Rong Wu, Chao Dang

“…Foreign objects caught and entangled on power grid transmission lines, power towers and other equipment can pose potential threats to the power system. The detection algorithm for foreign objects in the power grid cannot achieve the optimal balance in terms of accuracy and efficiency. …”
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Enhancing Kalman Filter Performance: Design and Estimation with Fading-Memory Kalman Filter for Reduced Modeling Error and Improved Robustness by Jalil Manafian, Mehdi Fazli, Onur Alp Ilhan, Somaye Malmir, Sukaina Tuama Ghafel

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Tomato Ripening Detection in Complex Environments Based on Improved BiAttFPN Fusion and YOLOv11-SLBA Modeling by Yan Hao, Lei Rao, Xueliang Fu, Hao Zhou, Honghui Li

“…This is a 3.4% improvement in accuracy, a 1.5% improvement in average precision, and a 1.6% improvement in F1-score when compared to the baseline model YOLOv11. …”
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Improving Event Data in Football Matches: A Case Study Model for Synchronizing Passing Events with Positional Data by Alberto Cortez, Bruno Gonçalves, João Brito, Hugo Folgado

“…Spatial accuracy also improved, with OSD showing reduced deviation from RSD compared to the original event data. …”
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Improved and Optimized GNSS-IR Sea Surface Height Retrieval Based on Noise Elimination and Lightweight Airborne Multi-GNSS Multi-UAV Fusion by Naiquan Zheng, Ying Xu, Fuxi Zhao, Mingzhen Xin, Fanlin Yang

“…The inversion accuracy of the improved model is better, which confirms the effectiveness of the improved GNSS-IR model based on intelligent extraction, decomposition and reconstruction of δSNR data. …”
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Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome by Pedro Pons-Suñer, François Signol, Noemi Alvarez, Claudia Sargas, Sara Dorado, Jose Vicente Gil Ortí, Juan A. Delgado Sanchis, Marta Llop, Laura Arnal, Rafael Llobet, Juan-Carlos Perez-Cortes, Rosa Ayala, Eva Barragán

“…First, to evaluate a feature selection methodology based on SEQENS, an algorithm for identifying relevant variables. Second, to validate machine learning models that predict the risk of complications in patients with acute myeloid leukemia (AML) using data available at diagnosis. …”
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Optimization and Verification of One-dimensional Three-field Model for Transient Analysis of Pressurized Water Reactor by YUAN Leqi1, LI Zanwang1, 2, FAN Jie1, 3, GOU Junli1, SHAN Jianqiang1

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