Vehicle speed measurement method using monocular cameras by Hao Lian, Meian Li, Ting Li, Yongan Zhang, Yanyu Shi, Yikun Fan, Wenqian Yang, Huilin Jiang, Peng Zhou, Haibo Wu

“…Finally, the algorithm is combined with You Only Look Once version 7 (YOLOv7) and Deep Simple Online and Realtime Tracking (DeepSORT) algorithms, integrating multiple model structures to optimize the network, achieving precise multi-target speed measurement. …”
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Tri-Algo guardian ensemble approach for fake news detection in social media by Borra Vineetha, Munirathinam Nirmala

“…An ensemble approach integrates multiple models to improve classification accuracy. …”
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Sustainability Study of Community Disaster Resilience Evolution Trends Based on Dissipative Structure Theory by Weijing Liang, Ye Xue

“…This study contributes by integrating multiple models and algorithms to assess community resilience, proposing a dynamic evolutionary model, and validating its feasibility through case studies. …”
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Shifts in precipitation regimes exacerbate global inequality in grassland nitrogen cycles by Miao Zheng, Jinglan Cui, Xiaoxi Wang, Xiuming Zhang, Zhongrui Xie, Ruoxi Zhang, Xinpeng Xu, Baojing Gu

“…By synthesizing 2944 experimental observations and integrating multiple models, here we show that under the middle-of-the-road scenario, global nitrogen input, harvest, and surplus from grasslands are projected to increase by 10, 7, and 3 million tonnes per year (Tg yr−1), respectively. …”
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Predictive Modeling for Electric Vehicle Battery State of Health: A Comprehensive Literature Review by Jianqiang Gong, Bin Xu, Fanghua Chen, Gang Zhou

“…Future research should focus on integrating multiple modeling methodologies to leverage their combined strengths, enhancing the collection of comprehensive battery lifecycle datasets to support robust model development, and extending the scope of SOH estimation beyond individual cells to encompass entire battery packs.…”
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Predictions of Muscle Forces During the Cross-Body Adduction and Hand-Behind-the-Back Tests to Assess Osteoarthritis of the Acromioclavicular Joint by Kamal Gautam, Mohamed Samir Hefzy, Kyle Behrens, Abdul A. Mustapha

“…Thus, this study underscores the necessity of integrating multiple modeling approaches and comprehensive validation, including experimental data, to enhance the accuracy and reliability of muscle force predictions in shoulder biomechanics during CBA and HBB tests.…”
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Enhancing pH prediction accuracy in Al2O3 gated ISFET using XGBoost regressor and stacking ensemble learning by Ashirbad Panda, Rishikesh Datar, Shreyas Deshpande, Gautam Bacher

“…A stacking ensemble learning approach was also implemented to integrate multiple models, enhancing prediction accuracy and thereby capturing additional information. …”
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Identification of neural crest and glial enhancers at the mouse Sox10 locus through transgenesis in zebrafish. by Anthony Antonellis, Jimmy L Huynh, Shih-Queen Lee-Lin, Ryan M Vinton, Gabriel Renaud, Stacie K Loftus, Gene Elliot, Tyra G Wolfsberg, Eric D Green, Andrew S McCallion, William J Pavan

“…To identify Sox10 cis-regulatory elements, we integrated multiple model systems, including cell-based screens and transposon-mediated transgensis in zebrafish, to scrutinize mammalian conserved, noncoding genomic segments at the mouse Sox10 locus. …”
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Early warning study of field station process safety based on VMD-CNN-LSTM-self-attention for natural gas load prediction by Wei Zhao, Bilin Shao, Ning Tian, Wen Zhang, Xue Zhao, Shuqiang Wu

“…By considering the benefits and feasibility of integrating multiple models, a VMD-CNN-LSTM-Self-Attention interval prediction method was innovatively proposed and developed. …”
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DOST: A consolidated health behavior model that maps factors influencing cancer screening uptake by Jyoshma Preema Dsouza, Stephan Van den Broucke

“…Conclusion By integrating multiple models, the DOST model offers a comprehensive framework that combines theoretical robustness with practical guidelines. …”
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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

“…The enhanced WAEL model effectively addresses the overfitting challenge by integrating multiple models that have gained unique insights from the data. …”
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Hybrid EXGBStackQoE Classifier and Stackelberg Game-Theoretic Approaches for Enhanced QoE in Video Services Over 5G Wireless Networks by K. B. Ajeyprasaath, Vetrivelan Pandu

“…This research addresses these limitations by introducing an advanced framework integrating multiple models and methodologies to enhance video QoE in 5G networks. …”
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The Inversion of SPAD Value in Pear Tree Leaves by Integrating Unmanned Aerial Vehicle Spectral Information and Textural Features by Ning Yan, Yasen Qin, Haotian Wang, Qi Wang, Fangyu Hu, Yuwei Wu, Xuedong Zhang, Xu Li

“…This study demonstrated the efficacy of integrating multiple models and features to accurately invert SPAD values, which, in turn, supported the refined management of pear orchards.…”
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Estimating and Downscaling ESA-CCI Soil Moisture Using Multi-Source Remote Sensing Images and Stacking-Based Ensemble Learning Algorithms in the Shandian River Basin, China by Liguo Wang, Ya Gao

“…Furthermore, it is observed that the stacking algorithm, which integrates multiple models, outperforms the single-model CatBoost algorithm in terms of accuracy. …”
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Error Classification and Static Detection Methods in Tri-Programming Models: MPI, OpenMP, and CUDA by Saeed Musaad Altalhi, Fathy Elbouraey Eassa, Sanaa Abdullah Sharaf, Ahmed Mohammed Alghamdi, Khalid Ali Almarhabi, Rana Ahmad Bilal Khalid

“…These models may be used independently or combined into dual- or tri-model applications to leverage their complementary strengths. However, integrating multiple models introduces subtle and difficult-to-detect runtime errors such as data races, deadlocks, and livelocks that often elude conventional compilers. …”
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The application of artificial intelligence models in predicting the risk of diabetic foot: a multicenter study by Yao Li, Siyuan Zhou, Bichen Ren, Shuai Ju, Xiaoyan Li, Wenqiang Li, Bingzhe Li, Yunmin Cai, Chunlei Chang, Lihong Huang, Zhihui Dong

“…The developed app integrates multiple models, compares their predictions for different clinical scenarios, and enhances prediction transparency and reliability.The multi-model approach demonstrates strong predictive performance for DF risk, offering clinicians an intuitive and accurate assessment tool tailored to individual patients. …”
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