Optimasi Model Extreme Gradient Boosting Dalam Upaya Penentuan Tingkat Risiko Pada Ibu Hamil Berbasis Bayesian Optimization (BOXGB) by Edi Jaya Kusuma, Ririn Nurmandhani, Lenci Aryani, Ika Pantiawati, Guruh Fajar Shidik

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Predicting Weaning Weight of Romanov Lambs From Biometric Measurements Before Weaning Age Using Machine Learning Algorithms by Mehmet Eroğlu, Ali Osman Turgut, Mürsel Küçük, Muhammed Furkan Önen

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Radiomic study of common sellar region lesions differentiation in magnetic resonance imaging based on multi-classification machine learning model by Hang Qu, Qiqi Ban, LiangXue Zhou, HaiHan Duan, Wei Wang, AiJun Peng

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Using a machine learning algorithm and clinical data to predict the risk factors of disease recurrence after adjuvant treatment of advanced-stage oral cavity cancer by Sheng-Yao Huang, Ren-Jun Hsu, Dai-Wei Liu, Wen-Lin Hsu

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Compressive Strength Prediction Using Coupled Deep Learning Model with Extreme Gradient Boosting Algorithm: Environmentally Friendly Concrete Incorporating Recycled Aggregate by Mayadah W. Falah, Sadaam Hadee Hussein, Mohammed Ayad Saad, Zainab Hasan Ali, Tan Huy Tran, Rania M. Ghoniem, Ahmed A. Ewees

“…Extreme gradient boosting (XGBoost) was integrated with the developed AI models to select the influencing variables on the CS prediction. …”
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Integrated Water Vapor Estimation During Clear Skies Using a Ground-Based Infrared Radiometer and the Light Gradient Boosting Machine Method by Wenyue Wang, Catalina Medina Porcile, Wenzhi Fan, Klemens Hocke

“…New algorithms of retrieving atmospheric integrated water vapor (IWV) under clear-sky conditions for the infrared radiometer using linear regression, quadratic regression (QR), and light gradient boosting machine (LightGBM) methods are developed in this work. …”
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Enhanced Light-Gradient Boosting Machine (GBM)-Based Artificial Intelligence-Blockchain-Based Telesurgery in Sixth Generation Communication Using Optimization Concept by Punitha S., Preetha K. S.

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Real Estate Appraisal Performance Improvement by Adapting a Hybrid Model: Geographically Weighted Regression and Extreme Gradient Boosting in Al Bireh, Palestine by Jamal A.A. Numan, Izham Mohamad Yusoff

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Forecast of NOx Emissions for a 660MW Coal-Fired Boiler with Multilayered Gradient Boosting Decision Tree Considering Multiple Operating Modes by Ziwei Wang, Yongzan Zhou, Yukun Zhu, Haiquan Yu, Wei Fan

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Comparing Gradient Boosting and Neural Networks in Predicting Age Based on Coronal Pulp Height from Panoramic Radiographs – A Retrospective Radiographic Study by Kishorwara Ramamoorthy, Devika S. Pillai, Pradeep Kumar Yadalam, Prasanthi Sitaraman

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Leveraging Advanced Mathematical Methods in Artificial Intelligence to Explore Heterogeneity and Asymmetry in Cross-Border Travel Satisfaction by Yan Xu, Huajie Yang, Zibin Ye, Xiaobo Ma, Lei Tong, Xinyi Yu

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Machine learning approach in predicting water saturation using well data at “TM” Niger Delta by Oluwakemi Y. Adeogun, Mukthar O. Abdulwaheed, Lukumon Adeoti, Olawale J. Allo, Olawunmi O. Fasakin, Oluwafemi O. Okunowo

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Computational intelligence modeling and optimization of small molecule API solubility in supercritical solvent for production of drug nanoparticles by Jiaxin Liang, Hai Zhao, Shengxue Zhou, Yang Gao

“…Ensemble models based on decision tree are selected to make models. The models include gradient boosting (GBDT), extremely randomized trees (ET), and random forest (RF) and tuned using ant colony optimization (ACO). …”
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Clinical and inflammatory features based machine learning model for fatal risk prediction of hospitalized COVID-19 patients: results from a retrospective cohort study by Xin Guan, Bo Zhang, Ming Fu, Mengying Li, Xu Yuan, Yaowu Zhu, Jing Peng, Huan Guo, Yanjun Lu

“…Further multi-tree extreme gradient boosting (XGBoost) machine learning-based model was used to rank importance of features selected from LASSO and subsequently constructed death risk prediction model with simple-tree XGBoost model. …”
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Creating High-Resolution Precipitation and Extreme Precipitation Indices Datasets by Downscaling and Improving on the ERA5 Reanalysis Data over Greece by Ntagkounakis Giorgos, Panagiotis T. Nastos, Yiannis Kapsomenakis

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Machine Learning Approaches for the Prediction of Displaced Abomasum in Dairy Cows Using a Highly Imbalanced Dataset by Zeinab Asgari, Ali Sadeghi-Sefidmazgi, Abbas Pakdel, Saleh Shahinfar

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Assessing groundwater level variability in response to climate change: A case study of large plain areas by Haidi Wu, Xueyan Ye, Xinqiang Du, Wuxiang Wang, Hongyan Li, Weihong Dong

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A case study on the application of a data-driven (XGBoost) approach on the environmental and socio-economic perspectives of agricultural groundwater management by Sheng-Wei Wang, Yen-Yu Chen, Shu-Han Hsu, Yu-Hsuan Kao, Masaomi Kimura, Li-chiu Chang, Tzi-Wen Pan, Chuen-Fa Ni

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Machine Learning-Based Forecasting Active Power Loss in Distribution Systems by Haider Waseem, Batool Seema, Milazzo Federica, Ha Quang P.

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Optimization of bioactive compounds and sensory quality in thermosonicated black carrot juice: A study using response surface methodology, gradient boosting, and fuzzy logic by Seydi Yıkmış, Melikenur Türkol, Ishak Pacal, Aylin Duman Altan, Nazlı Tokatlı, Gholamreza Abdi, Nazan Tokatlı Demirok, Rana Muhammad Aadil

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